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22 pages, 5016 KiB

Open AccessArticle

The Simultaneous Impact of EV Charging and PV Inverter Reactive Power on the Hosting Distribution System’s Performance: A Case Study in Kuwait

by Heba M. Abdullah, Rashad M. Kamel, Anas Tahir, Azzam Sleit and Adel Gastli

Energies 2020, 13(17), 4409; https://0-doi-org.brum.beds.ac.uk/10.3390/en13174409 - 26 Aug 2020

Cited by 4 | Viewed by 2611

Abstract

Recently, electric vehicles (EVs) have become an increasingly important topic in the field of sustainable transportation research, alongside distributed generation, reactive power compensation, charging optimization, and control. The process of loading on existing power system infrastructures with increasing demand requires appropriate impact indices [...] Read more.

Recently, electric vehicles (EVs) have become an increasingly important topic in the field of sustainable transportation research, alongside distributed generation, reactive power compensation, charging optimization, and control. The process of loading on existing power system infrastructures with increasing demand requires appropriate impact indices to be analyzed. This paper studies the impact of integrating electric vehicle charging stations (EVCSs) into a residential distribution network. An actual case study is modeled to acquire nodal voltages and feeder currents. The model obtains the optimal integration of solar photovoltaic (PV) panels with charging stations while considering reactive power compensation. The impact of EV integration for the case study results in two peaks, which show a 6.4% and 17% increase. Varying the inverter to the PV ratio from 1.1 to 2 decreases system losses by 34% to 41%. The type of charging is dependent on the maximum penetration of EVCSs that the network can install without system upgrades. Increasing the number of EVCSs can cause an increase in power system losses, which is dependent on the network architecture. Installing PV reduces the load peak by 21%, and the installation of PV with consideration of reactive power control increases system efficiency and power delivery. Full article

(This article belongs to the Special Issue Electric Systems for Transportation)

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29 pages, 6589 KiB

Open AccessArticle

Synergies between e-Mobility and Photovoltaic Potentials—A Case Study on an Urban Medium Voltage Grid

by Julia Vopava, Ulrich Bergmann and Thomas Kienberger

Energies 2020, 13(15), 3795; https://0-doi-org.brum.beds.ac.uk/10.3390/en13153795 - 23 Jul 2020

Cited by 7 | Viewed by 1954

Abstract

To reduce CO₂ emissions, it is necessary to cover the increasing energy demand of e-mobility with renewable energy sources. Therefore, the influence of increasing e-mobility and synergy effects between e-mobility and renewable energy sources need to be investigated. The case study presented [...] Read more.

To reduce CO₂ emissions, it is necessary to cover the increasing energy demand of e-mobility with renewable energy sources. Therefore, the influence of increasing e-mobility and synergy effects between e-mobility and renewable energy sources need to be investigated. The case study presented here shows results from the analysis of grid-side and energetic synergy effects between e-mobility charged only at work and photovoltaic (PV) potentials. The basis of the grid study is a simplified cell-based grid model. Following the determination of synthetic charging profiles for e-mobility, PV potential profiles, load and production profiles, we perform load flow calculations for different scenarios and a simulation period of one year using the grid model. After the grid study, the energy analyses are carried out using four key performance indicators. The grid study shows that line overloads caused by PV production are only reduced and not avoided by increasing e-mobility and vice versa. The increase in the power peak of e-mobility, by shifting the charging processes into the peak of PV potentials, leads to a reduction of the production surplus in summer, while in winter the line utilisation increases. By modelling PV potentials on real irradiation and temperature data, the investigation of key performance indicators can identify not only seasonal fluctuations but also daily fluctuations. Full article

(This article belongs to the Special Issue Electric Systems for Transportation)

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18 pages, 1314 KiB

Open AccessArticle

Comparative Analysis of National Policies for Electric Vehicle Uptake Using Econometric Models

by Jia Yao, Siqin Xiong and Xiaoming Ma

Energies 2020, 13(14), 3604; https://0-doi-org.brum.beds.ac.uk/10.3390/en13143604 - 13 Jul 2020

Cited by 12 | Viewed by 4288

Abstract

As electric vehicles (EVs) have been widely discussed as a promising way to mitigate the effect of climate change, various policies have been implemented across the world to promote the uptake of EVs. Policymakers also paid attention to the density of public charging [...] Read more.

As electric vehicles (EVs) have been widely discussed as a promising way to mitigate the effect of climate change, various policies have been implemented across the world to promote the uptake of EVs. Policymakers also paid attention to the density of public charging points. In this paper, we examined the impact of policies on EV markets in the post subsidy era with multiple linear regression analysis using panel data on 13 countries from 2015 to 2018. Five of the independent variables showed significantly positive effects on the 1% level in different regression models: fast/slow charger density, mandate, purchasing restriction and waiver. Subsidies showed significance only on 5% level for battery electric vehicles (BEVs). Financial stimulates have experienced a declining marginal effect, whereas a high density of fast chargers has the most significantly positive effect on EV uptake. This paper suggests policymakers can invest more in completing the public infrastructures of EVs, especially on fast charging points. Full article

(This article belongs to the Special Issue Electric Systems for Transportation)

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15 pages, 5325 KiB

Open AccessArticle

Development of Enhancing Battery Management for Reusing Automotive Lithium-Ion Battery

by Wen-Poo Yuan, Se-Min Jeong, Wu-Yang Sean and Yi-Hsien Chiang

Energies 2020, 13(13), 3306; https://0-doi-org.brum.beds.ac.uk/10.3390/en13133306 - 28 Jun 2020

Cited by 9 | Viewed by 2273

Abstract

In this study, a battery management system (BMS) is developed for reused lithium-ion battery (RLIB). Additional enhancing functions of battery management are established, i.e., estimation of life-sensitized parameters and life extension. Life-sensitizing parameters mainly include open-circuit voltage (OCV) and internal resistances (IRs). They [...] Read more.

In this study, a battery management system (BMS) is developed for reused lithium-ion battery (RLIB). Additional enhancing functions of battery management are established, i.e., estimation of life-sensitized parameters and life extension. Life-sensitizing parameters mainly include open-circuit voltage (OCV) and internal resistances (IRs). They are sensitized parameters individually relative to state of charge (SOC) and state of health (SOH). For estimating these two parameters, an adaptive control scheme is implemented in BMS. This online adaptive control approach has been extensively applied to nonlinear systems with uncertainties. In two experiments, OCV and IRs of reused battery packs are accurately extracted from working voltage and discharge current. An offline numerical model using a schematic method is applied to verify the applicability and efficiency of this proposed online scheme. Furthermore, a solution of actively extending life by using an ultracapacitor to share peak power of RLIB through adjusting duty ratio is also proposed. It is shown that this enhancing battery management for RLIB can properly estimate OCV and IRs, and actively extend the life of the RLIB in two experiments. Full article

(This article belongs to the Special Issue Electric Systems for Transportation)

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28 pages, 4746 KiB

Open AccessArticle

Total Cost of Ownership Model and Significant Cost Parameters for the Design of Electric Bus Systems

by Anders Grauers, Sven Borén and Oscar Enerbäck

Energies 2020, 13(12), 3262; https://0-doi-org.brum.beds.ac.uk/10.3390/en13123262 - 24 Jun 2020

Cited by 13 | Viewed by 4195

Abstract

Without experiences of electric buses, public transport authorities and bus operators have faced questions about how to implement them in a cost-effective way. Simple cost modelling cannot show how costs for different types of electric buses differ between different routes and timetables. Tools [...] Read more.

Without experiences of electric buses, public transport authorities and bus operators have faced questions about how to implement them in a cost-effective way. Simple cost modelling cannot show how costs for different types of electric buses differ between different routes and timetables. Tools (e.g., HASTUS, PtMS, and optibus) which can analyse such details are complicated, time consuming to use, and provide insufficient insights into the mechanisms that influence the cost. This paper therefore proposes a method for how to calculate total cost of ownership, for different types of electric buses, in a way which can predict how the cost varies based on route and timetable. The method excludes factors which cause minor cost variations in an almost random manor, in order to better show the fundamental mechanisms influencing different costs. The method will help in finding ways to reduce the cost and help to define a few cases which deserve a deep analysis with more complete tools. Testing of the method in a Swedish context showed that the results are in line with other theoretical and practical studies, and how the total cost of ownership can vary depending on the variables. Full article

(This article belongs to the Special Issue Electric Systems for Transportation)

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11 pages, 3652 KiB

Open AccessArticle

Impact of Intersection Control on Battery Electric Vehicle Energy Consumption

by Kyoungho Ahn, Sangjun Park and Hesham A. Rakha

Energies 2020, 13(12), 3190; https://0-doi-org.brum.beds.ac.uk/10.3390/en13123190 - 19 Jun 2020

Cited by 6 | Viewed by 2078

Abstract

Battery electric vehicle (BEV) sales have significantly increased in recent years. They have different energy consumption patterns compared to the fuel consumption patterns of internal combustion engine vehicles (ICEVs). This study quantified the impact of intersection control approaches—roundabout, traffic signal, and two-way stop [...] Read more.

Battery electric vehicle (BEV) sales have significantly increased in recent years. They have different energy consumption patterns compared to the fuel consumption patterns of internal combustion engine vehicles (ICEVs). This study quantified the impact of intersection control approaches—roundabout, traffic signal, and two-way stop controls—on BEVs’ energy consumption. The paper systematically investigates BEVs’ energy consumption patterns compared to the fuel consumption of ICEVs. The results indicate that BEVs’ energy consumption patterns are significantly different than ICEVs’ patterns. For example, for BEVs approaching a high-speed intersection, the roundabout was found to be the most energy-efficient intersection control, while the two-way stop sign was the least efficient. In contrast, for ICEVs, the two-way stop sign was the most fuel-efficient control, while the roundabout was the least efficient. Findings also indicate that the energy saving of traffic signal coordination was less significant for BEVs compared to the fuel consumption of ICEVs since more regenerative energy is produced when partial or poorly coordinated signal plans are implemented. The study confirms that BEV regenerative energy is a major factor in energy efficiency, and that BEVs recover different amounts of energy in different urban driving environments. The study suggests that new transportation facilities and control strategies should be designed to enhance BEVs’ energy efficiency, particularly in zero emission zones. Full article

(This article belongs to the Special Issue Electric Systems for Transportation)

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15 pages, 7546 KiB

Open AccessArticle

Optimization of Vehicle Braking Distance Using a Fuzzy Controller

by Peter Girovský, Jaroslava Žilková and Ján Kaňuch

Energies 2020, 13(11), 3022; https://0-doi-org.brum.beds.ac.uk/10.3390/en13113022 - 11 Jun 2020

Cited by 11 | Viewed by 2968

Abstract

The paper presents the study of an anti-lock braking system (ABS) that has been complemented by a fuzzy controller. The fuzzy controller was used to improve the braking performance of the vehicle, particularly in critical situations, for example, when braking a vehicle on [...] Read more.

The paper presents the study of an anti-lock braking system (ABS) that has been complemented by a fuzzy controller. The fuzzy controller was used to improve the braking performance of the vehicle, particularly in critical situations, for example, when braking a vehicle on wet road. The controller for the ABS was designed in the MATLAB/Simulink program. The designed controller was simulated on a medium-size vehicle model. During testing, three braking systems were simulated on the vehicle model. We compared the performance of a braking system without an ABS, a system with a threshold-based conventional ABS, and a braking system with the proposed ABS with a fuzzy controller. These three braking systems were simulation tested during braking the vehicle on a dry straight road and on a road with combined road adhesion. A maneuverability test was conducted, where the vehicle had to avoid an obstacle while braking. The results of each test are provided at the end of the paper. Full article

(This article belongs to the Special Issue Electric Systems for Transportation)

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19 pages, 4743 KiB

Open AccessArticle

Battery Management Systems—Challenges and Some Solutions

by Balakumar Balasingam, Mostafa Ahmed and Krishna Pattipati

Energies 2020, 13(11), 2825; https://0-doi-org.brum.beds.ac.uk/10.3390/en13112825 - 02 Jun 2020

Cited by 70 | Viewed by 10788

Abstract

Electric vehicles are set to be the dominant form of transportation in the near future and Lithium-based rechargeable battery packs have been widely adopted in them. Battery packs need to be constantly monitored and managed in order to maintain the safety, efficiency and [...] Read more.

Electric vehicles are set to be the dominant form of transportation in the near future and Lithium-based rechargeable battery packs have been widely adopted in them. Battery packs need to be constantly monitored and managed in order to maintain the safety, efficiency and reliability of the overall electric vehicle system. A battery management system consists of a battery fuel gauge, optimal charging algorithm, and cell/thermal balancing circuitry. It uses three non-invasive measurements from the battery, voltage, current and temperature, in order to estimate crucial states and parameters of the battery system, such as battery impedance, battery capacity, state of charge, state of health, power fade, and remaining useful life. These estimates are important for the proper functioning of optimal charging algorithms, charge and thermal balancing strategies, and battery safety mechanisms. Approach to robust battery management consists of accurate characterization, robust estimation of battery states and parameters, and optimal battery control strategies. This paper describes some recent approaches developed by the authors towards developing a robust battery management system. Full article

(This article belongs to the Special Issue Electric Systems for Transportation)

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15 pages, 924 KiB

Open AccessArticle

Multidispatch for Microgrid including Renewable Energy and Electric Vehicles with Robust Optimization Algorithm

by Ruifeng Shi, Penghui Zhang, Jie Zhang, Li Niu and Xiaoting Han

Energies 2020, 13(11), 2813; https://0-doi-org.brum.beds.ac.uk/10.3390/en13112813 - 02 Jun 2020

Cited by 10 | Viewed by 2183

Abstract

With the deterioration of the environment and the depletion of fossil fuel energy, renewable energy has attracted worldwide attention because of its continuous availability from nature. Despite this continuous availability, the uncertainty of intermittent power is a problem for grid dispatching. This paper [...] Read more.

With the deterioration of the environment and the depletion of fossil fuel energy, renewable energy has attracted worldwide attention because of its continuous availability from nature. Despite this continuous availability, the uncertainty of intermittent power is a problem for grid dispatching. This paper reports on a study of the scheduling and optimization of microgrid systems for photovoltaic (PV) power and electric vehicles (EVs). We propose a mathematical model to address the uncertainty of PV output and EV charging behavior, and model scheduling optimization that minimizes the economic and environmental cost of a microgrid system. A semi-infinite dual optimization model is then used to deal with the uncertain variables, which can be solved with a robust optimization algorithm. A numerical case study shows that the security and stability of the solution obtained by robust optimization outperformed that of stochastic optimization. Full article

(This article belongs to the Special Issue Electric Systems for Transportation)

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15 pages, 2339 KiB

Open AccessArticle

A Publicly Available Simulation of Battery Electric, Hybrid Electric, and Gas-Powered Vehicles

by Lawrence Fulton

Energies 2020, 13(10), 2569; https://0-doi-org.brum.beds.ac.uk/10.3390/en13102569 - 19 May 2020

Cited by 6 | Viewed by 3886

Abstract

Volatility in energy markets has made the purchase of battery electric vehicles (BEV) or hybrid vehicles (HEVs) attractive versus internal combustion engine vehicles (ICEVs). However, the total cost of ownership (TCO) and true environmental effects, are difficult to assess. This study provides a [...] Read more.

Volatility in energy markets has made the purchase of battery electric vehicles (BEV) or hybrid vehicles (HEVs) attractive versus internal combustion engine vehicles (ICEVs). However, the total cost of ownership (TCO) and true environmental effects, are difficult to assess. This study provides a publicly available, user-driven simulation that estimates the consumer and environmental costs for various vehicle purchase options, supporting policymaker, producer, and consumer information requirements. It appears to be the first to provide a publicly available, user interactive simulation that compares two purchase options simultaneously. It is likely that the first paper to simulate the effects of solar recharging of electric vehicles (EV) on both cost-benefit for the consumer and environmental benefit (e.g., carbon dioxide, oxides of nitrogen, non-methane organic gasses, particulate matter, and formaldehyde) simultaneously, demonstrating how, as an example, solar-based charging of BEVs and HEVs reduces carbon emissions over grid-based charging. Two specific scenarios are explicated, and the results of show early break-even for both BEV and Plug-in HEV (PHEV) options over ICEV (13 months, and 12 months, respectively) with CO₂ emissions about ½ that of the gasoline option (including production emissions.) The results of these simulations are congruent with previous research that identified quick break-even for HEVs versus ICEV. Full article

(This article belongs to the Special Issue Electric Systems for Transportation)

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15 pages, 4448 KiB

Open AccessArticle

Optimal Energy Management of Plug-In Hybrid Electric Vehicles Concerning the Entire Lifespan of Lithium-Ion Batteries

by Zeyu Chen, Jiahuan Lu, Bo Liu, Nan Zhou and Shijie Li

Energies 2020, 13(10), 2543; https://0-doi-org.brum.beds.ac.uk/10.3390/en13102543 - 17 May 2020

Cited by 14 | Viewed by 3491

Abstract

The performance of lithium-ion batteries will inevitably degrade during the high frequently charging/discharging load applied in electric vehicles. For hybrid electric vehicles, battery aging not only declines the performance and reliability of the battery itself, but it also affects the whole energy efficiency [...] Read more.

The performance of lithium-ion batteries will inevitably degrade during the high frequently charging/discharging load applied in electric vehicles. For hybrid electric vehicles, battery aging not only declines the performance and reliability of the battery itself, but it also affects the whole energy efficiency of the vehicle since the engine has to participate more. Therefore, the energy management strategy is required to be adjusted during the entire lifespan of lithium-ion batteries to maintain the optimality of energy economy. In this study, tests of the battery performances under thirteen different aging stages are involved and a parameters-varying battery model that represents the battery degradation is established. The influences of battery aging on energy consumption of a given plug-in hybrid electric vehicle (PHEV) are analyzed quantitatively. The results indicate that the variations of capacity and internal resistance are the main factors while the polarization and open circuit voltage (OCV) have a minor effect on the energy consumption. Based on the above efforts, the optimal energy management strategy is proposed for optimizing the energy efficiency concerning both the fresh and aging batteries in PHEV. The presented strategy is evaluated by a simulation study with different driving cycles, illustrating that it can balance out some of the harmful effects that battery aging can have on energy efficiency. The energy consumption is reduced by up to 2.24% compared with that under the optimal strategy without considering the battery aging. Full article

(This article belongs to the Special Issue Electric Systems for Transportation)

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34 pages, 4517 KiB

Open AccessArticle

Modular Isolated DC-DC Converters for Ultra-Fast EV Chargers: A Generalized Modeling and Control Approach

by Mena ElMenshawy and Ahmed Massoud

Energies 2020, 13(10), 2540; https://0-doi-org.brum.beds.ac.uk/10.3390/en13102540 - 17 May 2020

Cited by 15 | Viewed by 3234

Abstract

Electric Vehicles (EVs) play a significant role in the reduction of CO₂ emissions and other health-threatening air pollutants Accordingly, several research studies are introduced owing to replacing conventional gasoline-powered vehicles with battery-powered EVs. However, the ultra-fast charging (UFC) of the battery pack [...] Read more.

Electric Vehicles (EVs) play a significant role in the reduction of CO₂ emissions and other health-threatening air pollutants Accordingly, several research studies are introduced owing to replacing conventional gasoline-powered vehicles with battery-powered EVs. However, the ultra-fast charging (UFC) of the battery pack or the rapid recharging of the battery requires specific demands, including both: the EV battery and the influence on the power grid. In this regard, advanced power electronics technologies are emerging significantly to replace the currently existing gas station infrastructures with the EV charging stations to move from conventional charging (range of hours) to UFC (range of minutes). Among these power electronics conversion systems, the DC-DC conversion stage plays an essential role in supplying energy to the EV via charging the EV’s battery. Accordingly, this paper aims to present possible architectures of connecting multiple Dual Active Bridge (DAB) units as the DC-DC stage of the EV fast charger and study their Small-Signal Modeling (SSM) and their control scheme. These are, namely, Input-Series Output-Series (ISOS), Input-Series Output-Parallel (ISOP), Input-Parallel Output-Parallel (IPOP), and Input-Parallel Output-Series (IPOS). The control scheme for each system is studied through controlling the output filter inductor current such that the current profile is based on Reflex Charging (RC). The main contribution of this paper can be highlighted in providing generalized SSM as well as providing a generalized control approach for the Input-Series Input-Parallel Output-Series Output-Parallel (ISIP-OSOP) connection. The generalized model is verified with three different architectures. The control strategy for each architecture is studied to ensure equal power sharing, where simulation results are provided to elucidate the presented concept considering a three-module ISOS, IPOP, ISOP, and IPOS DC-DC converters. Full article

(This article belongs to the Special Issue Electric Systems for Transportation)

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18 pages, 3269 KiB

Open AccessArticle

Research on the Fault Diagnosis of a Polymer Electrolyte Membrane Fuel Cell System

by Feng Han, Ying Tian, Qiang Zou and Xin Zhang

Energies 2020, 13(10), 2531; https://0-doi-org.brum.beds.ac.uk/10.3390/en13102531 - 16 May 2020

Cited by 10 | Viewed by 2450

Abstract

In this work, the possibilistic fuzzy C-means clustering artificial bee colony support vector machine (PFCM-ABC-SVM) method is proposed and applied for the fault diagnosis of a polymer electrolyte membrane (PEM) fuel cell system. The innovation of this method is that it can filter [...] Read more.

In this work, the possibilistic fuzzy C-means clustering artificial bee colony support vector machine (PFCM-ABC-SVM) method is proposed and applied for the fault diagnosis of a polymer electrolyte membrane (PEM) fuel cell system. The innovation of this method is that it can filter data with Gaussian noise and diagnose faults under dynamic conditions, and the amplitude of characteristic parameters is reduced to ±10%. Under dynamic conditions with Gaussian noise, the faults of the PEM fuel cell system are simulated and the original dataset is established. The possibilistic fuzzy C-means (PFCM) algorithm is used to filter samples with membership and typicality less than 90% and to optimize the original dataset. The artificial bee colony (ABC) algorithm is used to optimize the penalty factor C and kernel function parameter g. Finally, the optimized support vector machine (SVM) model is used to diagnose the faults of the PEM fuel cell system. To illustrate the results of the fault diagnosis, a nonlinear PEM fuel cell simulator model which has been presented in the literature is used. In addition, the PFCM-ABC-SVM method is compared with other methods. The result shows that the method can diagnose faults in a PEM fuel cell system effectively and the accuracy of the testing set sample is up to 98.51%. When solving small-sized, nonlinear, high-dimensional problems, the PFCM-ABC-SVM method can improve the accuracy of fault diagnosis. Full article

(This article belongs to the Special Issue Electric Systems for Transportation)

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11 pages, 4329 KiB

Open AccessArticle

Durability and Reliability of EV Batteries under Electric Utility Grid Operations: Impact of Frequency Regulation Usage on Cell Degradation

by George Baure and Matthieu Dubarry

Energies 2020, 13(10), 2494; https://0-doi-org.brum.beds.ac.uk/10.3390/en13102494 - 15 May 2020

Cited by 13 | Viewed by 2608

Abstract

The usage of electric vehicle batteries to assist the main electric grid for the storage of energy provided by intermittent sources should become an essential tool to increase the penetration of green energies. However, this service induces additional usage on the cells and, [...] Read more.

The usage of electric vehicle batteries to assist the main electric grid for the storage of energy provided by intermittent sources should become an essential tool to increase the penetration of green energies. However, this service induces additional usage on the cells and, therefore, could degrade them further. Since degradation is path-dependent, it is of paramount importance to test the impact of all the different grid applications on the batteries. In this work, we tested the additional usage induced by using electric vehicle batteries for frequency regulation at moderate rates during rest or charge and found no detrimental effect after around 2000 cycles on the cells. Full article

(This article belongs to the Special Issue Electric Systems for Transportation)

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24 pages, 4098 KiB

Open AccessEditor’s ChoiceArticle

The Role of Powertrain Electrification in Achieving Deep Decarbonization in Road Freight Transport

by Juan C. González Palencia, Van Tuan Nguyen, Mikiya Araki and Seiichi Shiga

Energies 2020, 13(10), 2459; https://0-doi-org.brum.beds.ac.uk/10.3390/en13102459 - 13 May 2020

Cited by 28 | Viewed by 4096

Abstract

Decarbonizing road freight transport is difficult due to its reliance on fossil fuel internal combustion engine vehicles (ICEVs). The role of powertrain electrification in achieving deep decarbonization in road freight transport was studied using a vehicle stock turnover model, focusing on Japan. Twelve [...] Read more.

Decarbonizing road freight transport is difficult due to its reliance on fossil fuel internal combustion engine vehicles (ICEVs). The role of powertrain electrification in achieving deep decarbonization in road freight transport was studied using a vehicle stock turnover model, focusing on Japan. Twelve vehicle types were considered; combining four powertrains, ICEV, hybrid electric vehicle (HEV), battery electric vehicle (BEV) and fuel cell electric vehicle (FCEV); and three vehicle size classes, normal, compact and mini-sized vehicles. A scenario-based approach was used; considering a Base scenario, and three alternative scenarios targeting powertrain electrification. Between 2012 and 2050, tank to wheel CO₂ emissions decrease 42.8% in the Base scenario, due to the reduction of vehicle stock, the improvement of vehicle fuel consumption and the adoption of HEVs. Diffusion of FCEVs in normal vehicles and BEVs in compact and mini-sized vehicles achieves the largest tank to wheel CO₂ emissions reductions, up to 44.6% compared with the 2050 baseline value. The net cash flow is positive over the whole time horizon, peaking at 6.7 billion USD/year in 2049 and reaching 6.6 billion USD/year by 2050. Powertrain electrification is not enough to achieve any of the CO₂ emissions reduction targets in road freight transport. Full article

(This article belongs to the Special Issue Electric Systems for Transportation)

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16 pages, 2473 KiB

Open AccessArticle

Battery Electric Vehicle Eco-Cooperative Adaptive Cruise Control in the Vicinity of Signalized Intersections

by Hao Chen and Hesham A. Rakha

Energies 2020, 13(10), 2433; https://0-doi-org.brum.beds.ac.uk/10.3390/en13102433 - 12 May 2020

Cited by 14 | Viewed by 2472

Abstract

This study develops a connected eco-driving controller for battery electric vehicles (BEVs), the BEV Eco-Cooperative Adaptive Cruise Control at Intersections (Eco-CACC-I). The developed controller can assist BEVs while traversing signalized intersections with minimal energy consumption. The calculation of the optimal vehicle trajectory is [...] Read more.

This study develops a connected eco-driving controller for battery electric vehicles (BEVs), the BEV Eco-Cooperative Adaptive Cruise Control at Intersections (Eco-CACC-I). The developed controller can assist BEVs while traversing signalized intersections with minimal energy consumption. The calculation of the optimal vehicle trajectory is formulated as an optimization problem under the constraints of (1) vehicle acceleration/deceleration behavior, defined by a vehicle dynamics model; (2) vehicle energy consumption behavior, defined by a BEV energy consumption model; and (3) the relationship between vehicle speed, location, and signal timing, defined by vehicle characteristics and signal phase and timing (SPaT) data shared under a connected vehicle environment. The optimal speed trajectory is computed in real-time by the proposed BEV eco-CACC-I controller, so that a BEV can follow the optimal speed while negotiating a signalized intersection. The proposed BEV controller was tested in a case study to investigate its performance under various speed limits, roadway grades, and signal timings. In addition, a comparison of the optimal speed trajectories for BEVs and internal combustion engine vehicles (ICEVs) was conducted to investigate the impact of vehicle engine types on eco-driving solutions. Lastly, the proposed controller was implemented in microscopic traffic simulation software to test its networkwide performance. The test results from an arterial corridor with three signalized intersections demonstrate that the proposed controller can effectively reduce stop-and-go traffic in the vicinity of signalized intersections and that the BEV Eco-CACC-I controller produces average savings of 9.3% in energy consumption and 3.9% in vehicle delays. Full article

(This article belongs to the Special Issue Electric Systems for Transportation)

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13 pages, 5003 KiB

Open AccessArticle

Design of a Low Torque Ripple Three-Phase SRM for Automotive Shift-by-Wire Actuator

by Grace Firsta Lukman, Xuan Son Nguyen and Jin-Woo Ahn

Energies 2020, 13(9), 2329; https://0-doi-org.brum.beds.ac.uk/10.3390/en13092329 - 07 May 2020

Cited by 12 | Viewed by 2991

Abstract

The shift-by-wire (SBW) system in vehicles aims to increase performance, safety, and comfort during driving. Switched reluctance motors (SRMs) are simple, resilient, and require only minimum maintenance; these factors make it a good option for use as an SBW actuator. Inherently, SRM generates [...] Read more.

The shift-by-wire (SBW) system in vehicles aims to increase performance, safety, and comfort during driving. Switched reluctance motors (SRMs) are simple, resilient, and require only minimum maintenance; these factors make it a good option for use as an SBW actuator. Inherently, SRM generates a higher torque ripple than other AC machines, which can lead to a deterioration of its function. In this paper, a non-uniform air-gap rotor structure combined with the careful positioning of holes near the pole surface is proposed to reduce the torque ripple. The finite element method (FEM) is employed to analyze the electromagnetic characteristics of the design. The proposed motor is manufactured, and experiments are done to verify the performance. The design alone can reduce the torque ripple by 7% and flatten the torque waveform. The experimental result shows that the proposed motor can achieve the desired performance. The estimated torque ripple from the experiment is 26.65%. Full article

(This article belongs to the Special Issue Electric Systems for Transportation)

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24 pages, 4295 KiB

Open AccessArticle

Route Guidance Strategies for Electric Vehicles by Considering Stochastic Charging Demands in a Time-Varying Road Network

by Yongxing Wang, Jun Bi, Chaoru Lu and Cong Ding

Energies 2020, 13(9), 2287; https://0-doi-org.brum.beds.ac.uk/10.3390/en13092287 - 05 May 2020

Cited by 14 | Viewed by 2153

Abstract

Electric vehicles (EVs) are being increasingly adopted because of global concerns about petroleum dependence and greenhouse gas emissions. However, their limited driving range results in increased charging demands with a stochastic characteristic in real-world situations, and the charging demands should be attributed toward [...] Read more.

Electric vehicles (EVs) are being increasingly adopted because of global concerns about petroleum dependence and greenhouse gas emissions. However, their limited driving range results in increased charging demands with a stochastic characteristic in real-world situations, and the charging demands should be attributed toward charging stations in time-varying road networks. To this end, this study proposes guidance strategies to provide efficient choice for charging stations and corresponding routes, and it includes the time-varying characteristic of road networks in problem formulation. Specifically, we propose two route guidance strategies from different perspectives based on the charging demand information. The first strategy focuses on the effects of the number of EVs on the charging stations’ operation, and the reachable charging stations with the fewest vehicles are selected as the heuristic suggested ones. The other strategy considers the travel cost of individual drivers and selects the charging stations nearest to the destination as heuristic suggested ones. Both strategies ensure that the selected charging stations can be reached in a time-varying road network. In addition, we carry out a simulation analysis to investigate the performance of the proposed route guidance strategies and introduce relevant insights and recommendations for the application of the strategies under various scenarios. Full article

(This article belongs to the Special Issue Electric Systems for Transportation)

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18 pages, 10351 KiB

Open AccessArticle

Optimized Fuel Economy Control of Power-Split Hybrid Electric Vehicle with Particle Swarm Optimization

by Hsiu-Ying Hwang and Jia-Shiun Chen

Energies 2020, 13(9), 2278; https://0-doi-org.brum.beds.ac.uk/10.3390/en13092278 - 05 May 2020

Cited by 20 | Viewed by 2628

Abstract

This research focused on real-time optimization control to improve the fuel consumption of power-split hybrid electric vehicles. Particle swarm optimization (PSO) was implemented to reduce fuel consumption for real-time optimization control. The engine torque was design-variable to manage the energy distribution of dual [...] Read more.

This research focused on real-time optimization control to improve the fuel consumption of power-split hybrid electric vehicles. Particle swarm optimization (PSO) was implemented to reduce fuel consumption for real-time optimization control. The engine torque was design-variable to manage the energy distribution of dual energy sources. The AHS II power-split hybrid electric system was used as the powertrain system. The hybrid electric vehicle model was built using Matlab/Simulink. The simulation was performed according to US FTP-75 regulations. The PSO design objective was to minimize the equivalent fuel rate with the driving system still meeting the dynamic performance requirements. Through dynamic vehicle simulation and PSO, the required torque value for the whole drivetrain system and corresponding high-efficiency engine operating point can be found. With that, the two motor/generators (M/Gs) supplemented the rest required torques. The composite fuel economy of the PSO algorithm was 46.8 mpg, which is a 9.4% improvement over the base control model. The PSO control strategy could quickly converge and that feature makes PSO a good fit to be used in real-time control applications. Full article

(This article belongs to the Special Issue Electric Systems for Transportation)

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21 pages, 6105 KiB

Open AccessArticle

Energy Consumption and Lifecycle Cost Analysis of Electric City Buses with Multispeed Gearboxes

by Antti Ritari, Jari Vepsäläinen, Klaus Kivekäs, Kari Tammi and Heikki Laitinen

Energies 2020, 13(8), 2117; https://0-doi-org.brum.beds.ac.uk/10.3390/en13082117 - 24 Apr 2020

Cited by 32 | Viewed by 4308

Abstract

This study investigates the potential of improving the energy efficiency and reducing the lifecycle costs of electric city buses with multispeed gearboxes. A two-speed dual clutch gearbox and a continuously variable transmission were studied and compared to a reference fixed gear ratio powertrain. [...] Read more.

This study investigates the potential of improving the energy efficiency and reducing the lifecycle costs of electric city buses with multispeed gearboxes. A two-speed dual clutch gearbox and a continuously variable transmission were studied and compared to a reference fixed gear ratio powertrain. A novel two-level optimization model was introduced. The top level involves an exhaustive search algorithm and quasi-static vehicle dynamic model for optimizing the two-speed gearbox gear ratios, utilizing efficiency maps for the electric motor and the inverter. The second level is an integer programming model, which finds an optimal gear shifting policy subject to constraints on hysteresis and gear shifting induced losses. The model was applied with a standard driving cycle and additionally with three measured cycles acquired from a prototype battery electric city bus operating on a daily schedule on a suburban route in Espoo, Finland. The results showed that a two-speed gearbox reduced energy consumption by 2–3.2%, depending on the driving cycle characteristics. On the other hand, the continuously variable transmission was found to increase consumption by 1.9–4.0% due to large losses of the belt mechanism. It was concluded that the two-speed gearbox is a cost-effective investment for electric city buses characterized by operation profiles with frequent acceleration and braking events. Full article

(This article belongs to the Special Issue Electric Systems for Transportation)

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23 pages, 5208 KiB

Open AccessArticle

Comparative Study of Powertrain Hybridization for Heavy-Duty Vehicles Equipped with Diesel and Gas Engines

by Ilya Kulikov, Andrey Kozlov, Alexey Terenchenko and Kirill Karpukhin

Energies 2020, 13(8), 2072; https://0-doi-org.brum.beds.ac.uk/10.3390/en13082072 - 21 Apr 2020

Cited by 10 | Viewed by 3381

Abstract

This article describes a study that aimed to estimate the fuel-saving potential possessed by the hybridization of conventional powertrains intended for heavy-duty vehicles based on diesel and natural gas fueled engines. The tools used for this analysis constitute mathematical models of vehicle dynamics [...] Read more.

This article describes a study that aimed to estimate the fuel-saving potential possessed by the hybridization of conventional powertrains intended for heavy-duty vehicles based on diesel and natural gas fueled engines. The tools used for this analysis constitute mathematical models of vehicle dynamics and the powertrain, including its components, i.e., the engine, electric drive, transmission, and energy storage system (ESS). The model of the latter, accompanied by experimental data, allowed for an analysis of employing a supercapacitor regarding the selection of its energy content and the interface between the traction electric drive and the ESS (in light of the wide voltage operating range of supercapacitors). The results revealed the influence of these factors on both the supercapacitor efficiency (during its operation within a powertrain) and the vehicle fuel economy. After implementation of the optimized ESS design within the experimentally validated vehicle model, simulations were conducted in several driving cycles. The results allowed us to compare the fuel economy provided by the hybridization for diesel and gas powertrains in different driving conditions, with different vehicle masses, taking into account the onboard auxiliary power consumption. Full article

(This article belongs to the Special Issue Electric Systems for Transportation)

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19 pages, 6595 KiB

Open AccessArticle

Developing Equivalent Consumption Minimization Strategy for Advanced Hybrid System-II Electric Vehicles

by Hsiu-Ying Hwang

Energies 2020, 13(8), 2033; https://0-doi-org.brum.beds.ac.uk/10.3390/en13082033 - 19 Apr 2020

Cited by 8 | Viewed by 2319

Abstract

Compared with conventional vehicles, hybrid electric vehicles (HEVs) have the advantage of high-energy conversion efficiency, which can have better fuel economy and lower emissions. The main issue of HEVs is how to develop an energy management strategy to achieve significantly better fuel efficiency. [...] Read more.

Compared with conventional vehicles, hybrid electric vehicles (HEVs) have the advantage of high-energy conversion efficiency, which can have better fuel economy and lower emissions. The main issue of HEVs is how to develop an energy management strategy to achieve significantly better fuel efficiency. In this research, the Equivalent Consumption Minimization Strategy (ECMS) was applied to optimize the performance of fuel consumption in the Advanced Hybrid System-II (AHS-II). Based on FTP-75 Test Procedure defined by the U.S. Environmental Protection Agency (EPA), a backward simulation module was established. The baseline simulation module with the rule-based control strategy was validated with the original fuel consumption data. Then, the module with ECMS followed the same control rules of engine on/off and mode selection, and the fuel consumption of ECMS was compared with the simulation results of the baseline model. The fuel economy improvements of ECMS in urban, highway driving pattern, and composite fuel economy were up to 8.5%, 7.7%, and 8.1%, respectively. The simulation results showed that the difference of motors’ working efficiency was only 1.2% between ECMS and baseline rule-based control strategies. The main reason of fuel consumption improvement was the engine operation chosen by ECMS, which provided better power distribution. Full article

(This article belongs to the Special Issue Electric Systems for Transportation)

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16 pages, 3803 KiB

Open AccessArticle

Optimal Location of Fast Charging Stations for Mixed Traffic of Electric Vehicles and Gasoline Vehicles Subject to Elastic Demands

by Hong Gao, Kai Liu, Xinchao Peng and Cheng Li

Energies 2020, 13(8), 1964; https://0-doi-org.brum.beds.ac.uk/10.3390/en13081964 - 16 Apr 2020

Cited by 12 | Viewed by 2862

Abstract

With the rapid development of electric vehicles (EVs), one of the urgent issues is how to deploy limited charging facilities to provide services for as many EVs as possible. This paper proposes a bilevel model to depict the interaction between traffic flow distribution [...] Read more.

With the rapid development of electric vehicles (EVs), one of the urgent issues is how to deploy limited charging facilities to provide services for as many EVs as possible. This paper proposes a bilevel model to depict the interaction between traffic flow distribution and the location of charging stations (CSs) in the EVs and gasoline vehicles (GVs) hybrid network. The upper level model is a maximum flow-covering model where the CSs are deployed on links with higher demands. The lower level model is a stochastic user equilibrium model under elastic demands (SUE-ED) that considers both demands uncertainty and perceived path constraints, which have a significant influence on the distribution of link flow. Besides the path travel cost, the utility of charging facilities, charging speed, and waiting time at CSs due to space capacity restraint are also considered for the EVs when making a path assignment in the lower level model. A mixed-integer nonlinear program is constructed, and the equivalence of SUE-ED is proven, where a heuristic algorithm is used to solve the model. Finally, the network trial and sensitivity analysis are carried out to illustrate the feasibility and effectiveness of the proposed model. Full article

(This article belongs to the Special Issue Electric Systems for Transportation)

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25 pages, 6999 KiB

Open AccessArticle

Adaptive Smoothing Power Following Control Strategy Based on an Optimal Efficiency Map for a Hybrid Electric Tracked Vehicle

by Baodi Zhang, Sheng Guo, Xin Zhang, Qicheng Xue and Lan Teng

Energies 2020, 13(8), 1893; https://0-doi-org.brum.beds.ac.uk/10.3390/en13081893 - 13 Apr 2020

Cited by 14 | Viewed by 2772

Abstract

The series hybrid electric powertrain is the main architecture of the hybrid electric tracked vehicle. For a series tracked hybrid electric bulldozer (HEB), frequent fluctuations of the engine working points, deviation of the genset working points from the pre-set target trajectory due to [...] Read more.

The series hybrid electric powertrain is the main architecture of the hybrid electric tracked vehicle. For a series tracked hybrid electric bulldozer (HEB), frequent fluctuations of the engine working points, deviation of the genset working points from the pre-set target trajectory due to an insufficient response, or interference of the hydraulic pump consumed torque, will all result in increased fuel consumption. To solve the three problems of fuel economy, an adaptive smooth power following (ASPF) control strategy based on an optimal efficiency map is proposed. The strategy combines a fuzzy adaptive filter algorithm with a genset’s optimal efficiency, which can adaptively smooth the working points of the genset and search the trajectory for the genset’s best efficiency when the hydraulic pump torque is involved. In this study, the proposed strategy was compared on the established HEB hardware in loop (HIL) platform with two other strategies: a power following strategy in a preliminarily practical application (PF1) and a typical power following strategy based on the engine minimum fuel consumption curve (PF2). The results of the comparison show that (1) the proposed approach can significantly reduce the fluctuation and pre-set trajectory deviation of the engine and generator working points; (2) the ASPF strategy achieves a 7.8% improvement in the equivalent fuel saving ratio (EFSR) over the PF1 strategy, and a 3.4% better ratio than the PF2 strategy; and (3) the ASPF strategy can be implemented online with a practical controller. Full article

(This article belongs to the Special Issue Electric Systems for Transportation)

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14 pages, 8864 KiB

Open AccessArticle

Examination of EV Abilities to Provide Vehicle-to-Home Service in Low Voltage Installation

by Paweł Kelm, Rozmysław Mieński, Irena Wasiak and Katarzyna Wojciechowska

Energies 2020, 13(7), 1851; https://0-doi-org.brum.beds.ac.uk/10.3390/en13071851 - 10 Apr 2020

Cited by 5 | Viewed by 2593

Abstract

This paper deals with the application of an electric vehicle (EV) motor inverter and its batteries as an energy storage device supporting the operation of home electrical installation. This additional functionality of EV is called a Vehicle-to-Home (V2H) service. Two kind of services [...] Read more.

This paper deals with the application of an electric vehicle (EV) motor inverter and its batteries as an energy storage device supporting the operation of home electrical installation. This additional functionality of EV is called a Vehicle-to-Home (V2H) service. Two kind of services are considered: a peak shaving and an emergency power supply. The simulation model developed in the PSCAD program is presented. It allows for the examination of the EV battery control and operation during EV driving and parking. Additionally, it allows an evaluation of the availability of home installation for the V2H service. Control algorithms enabling the implementation of discussed work options are presented. Results of simulations are presented illustrating the EV control and operation in different operational modes. Full article

(This article belongs to the Special Issue Electric Systems for Transportation)

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24 pages, 3652 KiB

Open AccessArticle

Assessment of the Worthwhileness of Efficient Driving in Railway Systems with High-Receptivity Power Supplies

by Alejandro Cunillera, Adrián Fernández-Rodríguez, Asunción P. Cucala, Antonio Fernández-Cardador and Maria Carmen Falvo

Energies 2020, 13(7), 1836; https://0-doi-org.brum.beds.ac.uk/10.3390/en13071836 - 10 Apr 2020

Cited by 7 | Viewed by 2438

Abstract

Eco-driving is one of the most important strategies for significantly reducing the energy consumption of railways with low investments. It consists of designing a way of driving a train to fulfil a target running time, consuming the minimum amount of energy. Most eco-driving [...] Read more.

Eco-driving is one of the most important strategies for significantly reducing the energy consumption of railways with low investments. It consists of designing a way of driving a train to fulfil a target running time, consuming the minimum amount of energy. Most eco-driving energy savings come from the substitution of some braking periods with coasting periods. Nowadays, modern trains can use regenerative braking to recover the kinetic energy during deceleration phases. Therefore, if the receptivity of the railway system to regenerate energy is high, a question arises: is it worth designing eco-driving speed profiles? This paper assesses the energy benefits that eco-driving can provide in different scenarios to answer this question. Eco-driving is obtained by means of a multi-objective particle swarm optimization algorithm, combined with a detailed train simulator, to obtain realistic results. Eco-driving speed profiles are compared with a standard driving that performs the same running time. Real data from Spanish high-speed lines have been used to analyze the results in two case studies. Stretches fed by 1 × 25 kV and 2 × 25 kV AC power supply systems have been considered, as they present high receptivity to regenerate energy. Furthermore, the variations of the two most important factors that affect the regenerative energy usage have been studied: train motors efficiency ratio and catenary resistance. Results indicate that the greater the catenary resistance, the more advantageous eco-driving is. Similarly, the lower the motor efficiency, the greater the energy savings provided by efficient driving. Despite the differences observed in energy savings, the main conclusion is that eco-driving always provides significant energy savings, even in the case of the most receptive power supply network. Therefore, this paper has demonstrated that efforts in improving regenerated energy usage must not neglect the role of eco-driving in railway efficiency. Full article

(This article belongs to the Special Issue Electric Systems for Transportation)

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18 pages, 6085 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

Electric Vehicle–Grid Integration with Voltage Regulation in Radial Distribution Networks

by Chong Cao, Zhouquan Wu and Bo Chen

Energies 2020, 13(7), 1802; https://0-doi-org.brum.beds.ac.uk/10.3390/en13071802 - 08 Apr 2020

Cited by 20 | Viewed by 2994

Abstract

In this paper, a vehicle–grid integration (VGI) control strategy for radial power distribution networks is presented. The control schemes are designed at both microgrid level and distribution level. At the VGI microgrid level, the available power capacity for electric vehicle (EV) charging is [...] Read more.

In this paper, a vehicle–grid integration (VGI) control strategy for radial power distribution networks is presented. The control schemes are designed at both microgrid level and distribution level. At the VGI microgrid level, the available power capacity for electric vehicle (EV) charging is optimally allocated for charging electric vehicles to meet charging requirements. At the distribution grid level, a distributed voltage compensation algorithm is designed to recover voltage violation when it happens at a distribution node. The voltage compensation is achieved through a negotiation between the grid-level agent and VGI microgrid agents using the alternating direction method of multipliers. In each negotiation round, individual agents pursue their own objectives. The computation can be carried out in parallel for each agent. The presented VGI control schemes are simulated and verified in a modified IEEE 37 bus distribution system. The simulation results are presented to show the effectiveness of the VGI control algorithms and the effect of algorithm parameters on the convergence of agent negotiation. Full article

(This article belongs to the Special Issue Electric Systems for Transportation)

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17 pages, 2998 KiB

Open AccessArticle

Comparison of SOC Estimation between the Integer-Order Model and Fractional-Order Model Under Different Operating Conditions

by Guoqing Jin, Lan Li, Yidan Xu, Minghui Hu, Chunyun Fu and Datong Qin

Energies 2020, 13(7), 1785; https://0-doi-org.brum.beds.ac.uk/10.3390/en13071785 - 07 Apr 2020

Cited by 25 | Viewed by 2498

Abstract

Accurate estimation of the state of charge (SOC) is an important criterion to prevent the batteries from being over-charged or over-discharged, and this assures an electric vehicle’s safety and reliability. To investigate the effect of different operating conditions on the SOC estimation results, [...] Read more.

Accurate estimation of the state of charge (SOC) is an important criterion to prevent the batteries from being over-charged or over-discharged, and this assures an electric vehicle’s safety and reliability. To investigate the effect of different operating conditions on the SOC estimation results, a dual-polarization model (DPM) and a fractional-order model (FOM) are established in this study, taking into account the prediction accuracy and structural complexity of a battery model. Based on these two battery equivalent circuit models (ECMs), a hybrid Kalman filter (HKF) algorithm is adopted to estimate the SOC of the battery; the algorithm comprehensively utilizes the ampere-hour (Ah) integration method, the Kalman filter (KF) algorithm, and the extended Kalman filter (EKF) algorithm. The SOC estimation results of the DPM and FOM, under the dynamic stress test (DST), federal urban driving schedule (FUDS), and hybrid pulse power characteristic (HPPC) cycle conditions, are compared and analyzed through six sets of experiments. Simulation results show that the SOC estimation accuracy of both the models is high and that the errors are within the range of ±0.06. Under any operating conditions, the SOC estimation error, based on the FOM, is always lower than the SOC estimation error of the DPM, but the adaptability of the FOM is not as high as that of the DPM. Full article

(This article belongs to the Special Issue Electric Systems for Transportation)

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23 pages, 10712 KiB

Open AccessArticle

Energy Efficiency Comparison of Hydraulic Accumulators and Ultracapacitors

by Jorge Leon-Quiroga, Brittany Newell, Mahesh Krishnamurthy, Andres Gonzalez-Mancera and Jose Garcia-Bravo

Energies 2020, 13(7), 1632; https://0-doi-org.brum.beds.ac.uk/10.3390/en13071632 - 02 Apr 2020

Cited by 13 | Viewed by 3853

Abstract

Energy regeneration systems are a key factor for improving energy efficiency in electrohydraulic machinery. This paper is focused on the study of electric energy storage systems (EESS) and hydraulic energy storage systems (HESS) for energy regeneration applications. Two test benches were designed and [...] Read more.

Energy regeneration systems are a key factor for improving energy efficiency in electrohydraulic machinery. This paper is focused on the study of electric energy storage systems (EESS) and hydraulic energy storage systems (HESS) for energy regeneration applications. Two test benches were designed and implemented to compare the performance of the systems under similar operating conditions. The electrical system was configured with a set of ultracapacitors, and the hydraulic system used a hydraulic accumulator. Both systems were designed to have the same energy storage capacity. Charge and discharge cycle experiments were performed for the two systems in order to compare their power density, energy density, cost, and efficiency. According to the experimentally obtained results, the power density in the hydraulic accumulator was 21.7% higher when compared with the ultracapacitors. Moreover, the cost/power ($/Watt) ratio in the hydraulic accumulator was 2.9 times smaller than a set of ultracapacitors of the same energy storage capacity. On the other hand, the energy density in the set of ultracapacitors was 9.4 times higher, and the cost/energy ($/kWh) ratio was 2.9 times smaller when compared with the hydraulic accumulator. Under the tested conditions, the estimated overall energy efficiency for the hydraulic accumulator was 87.7%, and the overall energy efficiency for the ultracapacitor was 78.7%. Full article

(This article belongs to the Special Issue Electric Systems for Transportation)

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18 pages, 4910 KiB

Open AccessArticle

LCC-S Based Discrete Fast Terminal Sliding Mode Controller for Efficient Charging through Wireless Power Transfer

by Naghmash Ali, Zhizhen Liu, Yanjin Hou, Hammad Armghan, Xiaozhao Wei and Ammar Armghan

Energies 2020, 13(6), 1370; https://0-doi-org.brum.beds.ac.uk/10.3390/en13061370 - 16 Mar 2020

Cited by 19 | Viewed by 2967

Abstract

Compared to the plug-in charging system, Wireless power transfer (WPT) is simpler, reliable, and user-friendly. Resonant inductive coupling based WPT is the technology that promises to replace the plug-in charging system. It is desired that the WPT system should provide regulated current and [...] Read more.

Compared to the plug-in charging system, Wireless power transfer (WPT) is simpler, reliable, and user-friendly. Resonant inductive coupling based WPT is the technology that promises to replace the plug-in charging system. It is desired that the WPT system should provide regulated current and power with high efficiency. Due to the instability in the connected load, the system output current, power, and efficiency vary. To solve this issue, a buck converter is implemented on the secondary side of the WPT system, which adjusts its internal resistance by altering its duty cycle. To control the duty cycle of the buck converter, a discrete fast terminal sliding mode controller is proposed to regulate the system output current and power with optimal efficiency. The proposed WPT system uses the LCC-S compensation topology to ensure a constant output voltage at the input of the buck converter. The LCC-S topology is analyzed using the two-port network theory, and governing equations are derived to achieve the maximum efficiency point. Based on the analysis, the proposed controller is used to track the maximum efficiency point by tracking an optimal power point. An ultra-capacitor is connected as the system load, and based on its charging characteristics, an optimal charging strategy is devised. The performance of the proposed system is tested under the MATLAB/Simulink platform. Comparison with the conventionally used PID and sliding mode controller under sudden variations in the connected load is presented and discussed. An experimental prototype is built to validate the effectiveness of the proposed controller. Full article

(This article belongs to the Special Issue Electric Systems for Transportation)

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19 pages, 4729 KiB

Open AccessArticle

Optimal Torque Distribution Control of Multi-Axle Electric Vehicles with In-wheel Motors Based on DDPG Algorithm

by Liqiang Jin, Duanyang Tian, Qixiang Zhang and Jingjian Wang

Energies 2020, 13(6), 1331; https://0-doi-org.brum.beds.ac.uk/10.3390/en13061331 - 13 Mar 2020

Cited by 13 | Viewed by 3508

Abstract

In order to effectively reduce the energy consumption of the vehicle, an optimal torque distribution control for multi-axle electric vehicles (EVs) with in-wheel motors is proposed. By analyzing the steering dynamics, the formulas of additional steering resistance are given. Aiming at the multidimensional [...] Read more.

In order to effectively reduce the energy consumption of the vehicle, an optimal torque distribution control for multi-axle electric vehicles (EVs) with in-wheel motors is proposed. By analyzing the steering dynamics, the formulas of additional steering resistance are given. Aiming at the multidimensional continuous system that cannot be solved by traditional optimization methods, the deep deterministic policy gradient (DDPG) algorithm for deep reinforcement learning is adopted. Each wheel speed and deflection angle are selected as the state, the distribution ratio of drive torque is the optimized action and the state of charge (SOC) is the reward. After completing a large number of training for vehicle model, the algorithm is verified under conventional steering and extreme steering conditions. The maximum SOC decline of the vehicle can be reduced by about 5% under conventional steering conditions based on the motor efficiency mapused. The combination of artificial intelligence technology and actual situation provides an innovative solution to the optimization problem of the multidimensional state input and the continuous action output related to vehicles or similar complex systems. Full article

(This article belongs to the Special Issue Electric Systems for Transportation)

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16 pages, 5532 KiB

Open AccessArticle

An Extremely High Power Density Asymmetrical Back-to-Back Converter for Aerospace Motor Drive Applications

by Yifan Zhang, Chushan Li, David Xu, Wuhua Li, Jian Zhang, Hao Ma and Xiangning He

Energies 2020, 13(5), 1292; https://0-doi-org.brum.beds.ac.uk/10.3390/en13051292 - 10 Mar 2020

Cited by 6 | Viewed by 3079

Abstract

Higher-voltage-standard and higher-power-rating aerospace power systems are being investigated intensively in the aerospace industry to address challenges in terms of improving emissions, fuel economy, and also cost. Multilevel converter topologies become attractive because of their higher efficiency under high-voltage and high-switching-frequency conditions. In [...] Read more.

Higher-voltage-standard and higher-power-rating aerospace power systems are being investigated intensively in the aerospace industry to address challenges in terms of improving emissions, fuel economy, and also cost. Multilevel converter topologies become attractive because of their higher efficiency under high-voltage and high-switching-frequency conditions. In this paper, an asymmetrical-voltage-level back-to-back multilevel converter is proposed, which consists of a five-level (5L) rectifier stage and a three-level (3L) inverter stage. Based on the comparison, such an asymmetrical back-to-back structure can achieve high efficiency and minimize the converter weight on both rectifier and inverter sides. A compact triple-surface-mounted heatsink structure is designed to realize high density and manufacturable thermal management. This topology and structure are evaluated with a full-rating prototype. According to the evaluation, the achieved power density is 2.61 kVA/kg, which is 30% higher than that of traditional solutions. The efficiency at the rated power of the back-to-back system is 95.8%. Full article

(This article belongs to the Special Issue Electric Systems for Transportation)

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12 pages, 4013 KiB

Open AccessArticle

Road Test-Based Electric Bus Selection: A Case Study of the Nanjing Bus Company

by Jian Gong, Jie He, Cheng Cheng, Mark King, Xintong Yan, Zhixia He and Hao Zhang

Energies 2020, 13(5), 1253; https://0-doi-org.brum.beds.ac.uk/10.3390/en13051253 - 08 Mar 2020

Cited by 11 | Viewed by 2896

Abstract

Globally, the use of electric vehicles, and in particular the use of electric buses, has been increasing. The city of Nanjing leads China in the adoption of electric buses, supported by city policies and infrastructure. To lower costs and provide a better service, [...] Read more.

Globally, the use of electric vehicles, and in particular the use of electric buses, has been increasing. The city of Nanjing leads China in the adoption of electric buses, supported by city policies and infrastructure. To lower costs and provide a better service, vehicle selection is crucial, however, existing selection methods are limited. Accordingly, Nanjing Bus Company developed a test method based on road tests to select a bus. This paper presents a detailed description of the test method and a case study of its application. The method included an organization structure, selection of eight test vehicles (four 10 m length, four 8 m length) from four brands (a total of 32 test vehicles), selection of indicators and selection of routes. Data was collected from repeated drives by 65 drivers over an 8-week period. Indicators included power consumption, charging duration, failure duration and driving distance. It is concluded that the road test method designed and conducted by the Nanjing Bus Company provides a good framework for the selection of pure electric buses. Furthermore, subsequent experience with selected buses supports the validity and value of the model. Full article

(This article belongs to the Special Issue Electric Systems for Transportation)

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Review

Jump to: Research

13 pages, 1140 KiB

Open AccessReview

Life Cycle Assessment of Electric Vehicle Batteries: An Overview of Recent Literature

by Andrea Temporelli, Maria Leonor Carvalho and Pierpaolo Girardi

Energies 2020, 13(11), 2864; https://0-doi-org.brum.beds.ac.uk/10.3390/en13112864 - 04 Jun 2020

Cited by 49 | Viewed by 14791

Abstract

In electric and hybrid vehicles Life Cycle Assessments (LCAs), batteries play a central role and are in the spotlight of scientific community and public opinion. Automotive batteries constitute, together with the powertrain, the main differences between electric vehicles and internal combustion engine vehicles. [...] Read more.

In electric and hybrid vehicles Life Cycle Assessments (LCAs), batteries play a central role and are in the spotlight of scientific community and public opinion. Automotive batteries constitute, together with the powertrain, the main differences between electric vehicles and internal combustion engine vehicles. For this reason, many decision makers and researchers wondered whether energy and environmental impacts from batteries production, can exceed the benefits generated during the vehicle’s use phase. In this framework, the purpose of the present literature review is to understand how large and variable the main impacts are due to automotive batteries’ life cycle, with particular attention to climate change impacts, and to support researchers with some methodological suggestions in the field of automotive batteries’ LCA. The results show that there is high variability in environmental impact assessment; CO₂eq emissions per kWh of battery capacity range from 50 to 313 g CO₂eq/kWh. Nevertheless, either using the lower or upper bounds of this range, electric vehicles result less carbon-intensive in their life cycle than corresponding diesel or petrol vehicles. Full article

(This article belongs to the Special Issue Electric Systems for Transportation)

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19 pages, 2568 KiB

Open AccessFeature PaperReview

A Review on Energy Efficiency in Three Transportation Sectors: Railways, Electrical Vehicles and Marine

by Morris Brenna, Vittorio Bucci, Maria Carmen Falvo, Federica Foiadelli, Alessandro Ruvio, Giorgio Sulligoi and Andrea Vicenzutti

Energies 2020, 13(9), 2378; https://0-doi-org.brum.beds.ac.uk/10.3390/en13092378 - 09 May 2020

Cited by 23 | Viewed by 4666

Abstract

The present paper is a review on efficiency issues related to three important sectors of the transportation systems: railways, electrical vehicles, and marine. For the three sectors, the authors, in reference of their knowledge and research area, show the results of a wide [...] Read more.

The present paper is a review on efficiency issues related to three important sectors of the transportation systems: railways, electrical vehicles, and marine. For the three sectors, the authors, in reference of their knowledge and research area, show the results of a wide literature analysis, in order to highlight which are the measures, in terms of technological solutions and management techniques, which are recently investigated and implemented, for improving the three transportation systems, from the point of view of efficiency. In particular, for the railway transportation sector, a wide analysis is presented, detecting which are the main measures adopted for improving the efficiency, related to the power systems for supplying trains and to the train traffic control, with a focus on the storage system integration. For electric road vehicles the analysis is focused on the plug-in electrical vehicles and on the infrastructure for their recharge, with an emphasis on how these vehicles can support the grid, e.g., through Vehicle to Grid (V2G) applications. Finally, for the marine transport service the review is related to the propulsion systems and on how the different solutions can meet the objective of efficiency. Full article

(This article belongs to the Special Issue Electric Systems for Transportation)

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