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Electric Vehicle Efficient Power and Propulsion Systems

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A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "E: Electric Vehicles".

Deadline for manuscript submissions: closed (31 March 2022) | Viewed by 40673

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Special Issue Editors

Prof. Dr. João Pedro F. Trovao

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Guest Editor

Department of Electrical and Computer Engineering, University of Sherbrooke, Sherbrooke, QC J1G 2E8, Canada
Interests: electric vehicles; artificial intelligence; energy management; multiple energy source; electric machines

Prof. Dr. Minh Cao Ta

E-Mail Website
Guest Editor

Department of Industrial Automation, Hanoi University of Science and Technology, Hanoi, Vietnam
Interests: electric drives; power electronics; control engineering; electric vehicles; renewable energy

Special Issue Information

Dear Colleagues,

Vehicle electrification is one of the main trends identified, with a growth capacity of 15% until 2030. In the coming years, many internal combustion engine vehicles, hybrid vehicles, and all-electric vehicles will be on the road as consumers switch to more efficient and environmentally friendly propulsion systems. To remain competitive in this electrically powered future, carmakers and researchers are investing in a wide range of propulsion technologies to increase efficiency and power capacity, developing the next generation of powertrains. The development of more efficient pure EVs, HEVs, and fuel cell electric vehicles (FCEV) presents both a challenge and a definite solution to current mobility issues. A reliable EV solution should therefore harness the advantages of more efficient and powerful energy storage systems, including multiple sources through their effective management, new improved power converters, including the new generation of switching devices, and explore advanced configurations for electric motors, reducing the use of rare-earth materials.

This Special Issue encourages researchers working in this field to share their latest developments in electric-vehicle-efficient power and propulsion systems, for road, rail, and air vehicles, both manned and unmanned. Topics of interest for publication include but are not limited to:

Energy storage systems:
- Design, system engineering, and specific applications in electric vehicles;
- X-management systems (battery, supercapacitors, fuel cell, etc.);
- State-of-charge and state-of-health estimation;
- Thermal-battery-management systems;
- Advanced energy storage technologies;
- Hybrid energy storage systems and applications;
- Power electronics for energy storage systems;
Power Electronics:
- Advanced systems based on SiC and GaN technologies;
- Multilevel inverter topologies and control;
- Recent DC/DC and DC/AC converter concepts;
- Conductive on-board and off-board charging systems;
- Modular and integrated power electronics systems;
- Design optimization of power electronics systems;
- Electric and electronic architectures for vehicles systems.
Electric machines:
- New design and further development of state-of-art machines;
- Modelling machines and drives;
- Advances in the field of control;
Energy management systems:
- Advanced rule-based methods, including deterministic and artificial intelligence;
- Advanced optimization methods, including global optimal and real-time near-optimal;
- Predictive techniques for real-time strategies;
- Machine learning, big data, and cloud computing for energy management;
- Combined sizing and energy management;
- New hybrid architectures and their management.

Prof. Dr. João Pedro F. Trovao
Prof. Dr. Minh Cao Ta
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

Hybrid and electric vehicles
Electrical power and energy systems
Vehicular energy management
Electrical machines and drives
Power electronics and energy conversion
Energy storage systems (battery, supercapacitor, fuel cells)
Hybrid energy storage system
Optimal control and energy management
Energy storage system sizing
Real-time optimal power management
Rule-based and machine learning methods

Published Papers (12 papers)

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Editorial

Jump to: Research

4 pages, 205 KiB

Open AccessEditorial

Electric Vehicle Efficient Power and Propulsion Systems

by João Pedro F. Trovão and Minh Cao Ta

Energies 2022, 15(11), 3863; https://0-doi-org.brum.beds.ac.uk/10.3390/en15113863 - 24 May 2022

Cited by 1 | Viewed by 1446

Abstract

Vehicle electrification is one of the main growing trends with an identified growth capacity of 15% until 2030 [...] Full article

(This article belongs to the Special Issue Electric Vehicle Efficient Power and Propulsion Systems)

Research

Jump to: Editorial

25 pages, 8978 KiB

Open AccessArticle

A Consensus Algorithm for Multi-Objective Battery Balancing

by Jorge Varela Barreras, Ricardo de Castro, Yihao Wan and Tomislav Dragicevic

Energies 2021, 14(14), 4279; https://0-doi-org.brum.beds.ac.uk/10.3390/en14144279 - 15 Jul 2021

Cited by 8 | Viewed by 3116

Abstract

Batteries stacks are made of cells in certain series-parallel arrangements. Unfortunately, cell performance degrades over time in terms of capacity, internal resistance, or self-discharge rate. In addition, degradation rates are heterogeneous, leading to cell-to-cell variations. Balancing systems can be used to equalize those differences. Dissipative or non-dissipative systems, so-called passive or active balancing, can be used to equalize either voltage at end-of-charge, or state-of-charge (SOC) at all times. While passive balancing is broadly adopted by industry, active balancing has been mostly studied in academia. Beyond that, an emerging research field is multi-functional balancing, i.e., active balancing systems that pursue additional goals on top of SOC equalization, such as equalization of temperature, power capability, degradation rates, or losses minimization. Regardless of their functionality, balancing circuits are based either on centralized or decentralized control systems. Centralized control entails difficult expandability and single point of failure issues, while decentralized control has severe controllability limitations. As a shift in this paradigm, here we present for the first time a distributed multi-objective control algorithm, based on a multi-agent consensus algorithm. We implement and validate the control in simulations, considering an electro-thermal lithium-ion battery model and an electric vehicle model parameterized with experimental data. Our results show that our novel multi-functional balancing can enhance the performance of batteries with substantial cell-to-cell differences under the most demanding operating conditions, i.e., aggressive driving and DC fast charging (2C). Driving times are extended (>10%), charging times are reduced (>20%), maximum cell temperatures are decreased (>10 °C), temperature differences are lowered (~3 °C rms), and the occurrence of low voltage violations during driving is reduced (>5×), minimizing the need for power derating and enhancing the user experience. The algorithm is effective, scalable, flexible, and requires low implementation and tuning effort, resulting in an ideal candidate for industry adoption. Full article

(This article belongs to the Special Issue Electric Vehicle Efficient Power and Propulsion Systems)

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30 pages, 5194 KiB

Open AccessArticle

Power Management Strategy of a Parallel Hybrid Three-Wheeler for Fuel and Emission Reduction

by Waruna Maddumage, Malika Perera, Rahula Attalage and Patrick Kelly

Energies 2021, 14(7), 1833; https://0-doi-org.brum.beds.ac.uk/10.3390/en14071833 - 25 Mar 2021

Cited by 7 | Viewed by 3003

Abstract

Millions of three-wheelers in large cities of Asia and Africa contribute to the already increasing urban air pollutants. An emerging method to reduce adverse effects of the growing three-wheeler fleet is hybrid-electric technology. The overall efficiency of a hybrid electric vehicle heavily depends on the power management strategy used in controlling the main powertrain components of the vehicle. Recent studies highlight the need for a comprehensive report on developing an easy-to-implement and efficient control strategy for hybrid electric three-wheelers. Thus, in the present study, a design methodology for a rule-based supervisory controller of a pre-transmission parallel hybrid three-wheeler based on an optimal control strategy (i.e., dynamic programming) is proposed. The optimal control problem for minimizing fuel, emissions (i.e., HC, CO and NOx) and gear shift frequency are solved using dynamic programming (DP). Numerical issues of DP are analyzed and trade-offs between optimizing objectives are presented. Since DP strategy cannot be implemented as a real-time controller, useful strategies are extracted to develop the proposed rule-based strategy. The developed rule-based strategy show performance within 10% of the DP results on WLTC and UDC-NEDC drive cycles and has the clear advantage of being near-optimal, easy-to-implement and computationally less demanding. Full article

(This article belongs to the Special Issue Electric Vehicle Efficient Power and Propulsion Systems)

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33 pages, 2187 KiB

Open AccessArticle

Co-Design of CVT-Based Electric Vehicles

by Caiyang Wei, Theo Hofman and Esin Ilhan Caarls

Energies 2021, 14(7), 1825; https://0-doi-org.brum.beds.ac.uk/10.3390/en14071825 - 25 Mar 2021

Cited by 11 | Viewed by 2856

Abstract

For an electric vehicle (EV) with a continuously variable transmission (CVT), a novel convex programming (CP)-based co-design method is proposed to minimize the total-cost-of-ownership (TCO). The integration of the electric machine (EM) and the CVT is the primary focus. The optimized system with co-design reduces the TCO by around 5.9% compared to a non-optimized CVT-based EV (based on off-the-shelf components) and by around 2% compared to the EV equipped with a single-speed transmission (SST). By taking advantage of the control and design freedom provided by the CVT, the optimal CVT, EM and battery sizes are found to reduce the system cost. It simultaneously finds the optimal CVT speed ratio and air-flow rate of the cooling system reducing the energy consumption. The strength of co-design is highlighted by comparing to a sequential design, and insights into the design of a low-power EV that is energy-efficient and cost-effective for urban driving are provided. A highly integrated EM-CVT system, which is efficient, low-cost and lightweight, can be expected for future EV applications. Full article

(This article belongs to the Special Issue Electric Vehicle Efficient Power and Propulsion Systems)

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17 pages, 1189 KiB

Open AccessArticle

Integrated Optimization of Routing and Energy Management for Electric Vehicles in Delivery Scheduling

by Lixing Wang, Zhenning Wu and Changyong Cao

Energies 2021, 14(6), 1762; https://0-doi-org.brum.beds.ac.uk/10.3390/en14061762 - 22 Mar 2021

Cited by 6 | Viewed by 2271

Abstract

At present, electric vehicles (EVs) are attracting increasing attention and have great potential for replacing fossil-fueled vehicles, especially for logistics applications. However, energy management for EVs is essential for them to be advantageous owing to their limitations with regard to battery capacity and recharging times. Therefore, inefficiencies can be expected for EV-based logistical operations without an energy management plan, which is not necessarily considered in traditional routing exercises. In this study, for the logistics application of EVs to manage energy and schedule the vehicle route, a system is proposed. The system comprises two parts: (1) a case-based reasoning subsystem to forecast the energy consumption and travel time for each route section, and (2) a genetic algorithm to optimize vehicle routing with an energy consumption situation as a new constraint. A dynamic adjustment algorithm is also adopted to achieve a rapid response to accidents in which the vehicles might be involved. Finally, a simulation is performed to test the system by adjusting the data from the vehicle routing problem with time windows. Solomon benchmarks are used for the validations. The analysis results show that the proposed vehicle management system is more economical than the traditional method. Full article

(This article belongs to the Special Issue Electric Vehicle Efficient Power and Propulsion Systems)

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28 pages, 5704 KiB

Open AccessArticle

Experimental Platform for Evaluation of On-Board Real-Time Motion Controllers for Electric Vehicles

by Thanh Vo-Duy, Minh C. Ta, Bảo-Huy Nguyễn and João Pedro F. Trovão

Energies 2020, 13(23), 6448; https://0-doi-org.brum.beds.ac.uk/10.3390/en13236448 - 06 Dec 2020

Cited by 5 | Viewed by 2958

Abstract

Electric vehicles are considered to be a greener and safer means of transport thanks to the distinguished advantages of electric motors. Studies on this object require experimental platforms for control validation purpose. Under the pressure of research, the development of these platforms must be reliable, safe, fast, and cost effective. To practically validate the control system, the controllers should be implemented in an on-board micro-controller platform; whereas, the vehicle model should be realized in a real-time emulator that behaves like the real vehicle. In this paper, we propose a signal hardware-in-the-loop simulation system for electric vehicles that are driven by four independent electric motors installed in wheels (in-wheel motor). The system is elaborately built on the basis of longitudinal, lateral, and yaw dynamics, as well as kinematic and position models, of which the characteristics are complete and comprehensive. The performance of the signal hardware-in-the-loop system is evaluated by various open-loop testing scenarios and by validation of a representative closed-loop optimal force distribution control. The proposed system can be applied for researches on active safety system of electric vehicles, including traction, braking control, force/torque distribution strategy, and electronic stability program. Full article

(This article belongs to the Special Issue Electric Vehicle Efficient Power and Propulsion Systems)

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19 pages, 4114 KiB

Open AccessArticle

Real-Time Energy Management of Parallel Hybrid Electric Vehicles Using Linear Quadratic Regulation

by Bảo-Huy Nguyễn, João Pedro F. Trovão, Ronan German and Alain Bouscayrol

Energies 2020, 13(21), 5538; https://0-doi-org.brum.beds.ac.uk/10.3390/en13215538 - 22 Oct 2020

Cited by 11 | Viewed by 2744

Abstract

Optimization-based methods are of interest for developing energy management strategies due to their high performance for hybrid electric vehicles. However, these methods are often complicated and may require strong computational efforts, which can prevent them from real-world applications. This paper proposes a novel real-time optimization-based torque distribution strategy for a parallel hybrid truck. The strategy aims to minimize the engine fuel consumption while ensuring battery charge-sustaining by using linear quadratic regulation in a closed-loop control scheme. Furthermore, by reformulating the problem, the obtained strategy does not require the information of the engine efficiency map like the previous works in literature. The obtained strategy is simple, straightforward, and therefore easy to be implemented in real-time platforms. The proposed method is evaluated via simulation by comparison to dynamic programming as a benchmark. Furthermore, the real-time ability of the proposed strategy is experimentally validated by using power hardware-in-the-loop simulation. Full article

(This article belongs to the Special Issue Electric Vehicle Efficient Power and Propulsion Systems)

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Graphical abstract

28 pages, 13683 KiB

Open AccessArticle

Longitudinal Modelling and Control of In-Wheel-Motor Electric Vehicles as Multi-Agent Systems

by Binh-Minh Nguyen, Hung Van Nguyen, Minh Ta-Cao and Michihiro Kawanishi

Energies 2020, 13(20), 5437; https://0-doi-org.brum.beds.ac.uk/10.3390/en13205437 - 18 Oct 2020

Cited by 13 | Viewed by 3972

Abstract

This paper deals with longitudinal motion control of electric vehicles (EVs) driven by in-wheel-motors (IWMs). It shows that the IWM-EV is fundamentally a multi-agent system with physical interaction. Three ways to model the IWM-EV are proposed, and each is applicable to certain control objectives. Firstly, a nonlinear model with hierarchical structure is established, and it can be used for passivity-based motion control. Secondly, a linearized model with rank-1 interconnection matrix is presented for stability analysis. Thirdly, a time-varying state-space model is proposed for optimal control using linear quadratic regulator (LQR). The proposed modellings contribute the new understanding of IWM-EV dynamics from the view point of multi-agent-system theory. By choosing the suitable control theory for each model, the complexity level of system design is maintained constant, no matter what the number of IWMs installed to the vehicle body. The effectiveness of three models and their design approaches are discussed by several examples with Matlab/Carsim co-simulator. Full article

(This article belongs to the Special Issue Electric Vehicle Efficient Power and Propulsion Systems)

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20 pages, 4960 KiB

Open AccessArticle

Impact of Powertrain Components Size and Degradation Level on the Energy Management of a Hybrid Industrial Self-Guided Vehicle

by Amin Ghobadpour, Ali Amamou, Sousso Kelouwani, Nadjet Zioui and Lotfi Zeghmi

Energies 2020, 13(19), 5041; https://0-doi-org.brum.beds.ac.uk/10.3390/en13195041 - 24 Sep 2020

Cited by 8 | Viewed by 2649

Abstract

This paper deals with the design of an energy management strategy (EMS) for an industrial hybrid self-guided vehicle (SGV), considering the size of a fuel cell (FC) stack and degradation of a battery pack. In this context, first, a realistic energy model of the SGV was proposed and validated, based on experiments. This model provided a basis for individual components analysis, estimating energy requirements, component sizing, and testing various EMSs, prior to practical implementation. Second, the performance of the developed FC/battery SGV powertrain was validated under three EMS modes. Each mode was studied by considering four different FC sizes and three battery degradation levels. The final results showed that a small FC as a range extender is recommended, to reduce system cost. It is also important to maintain the FC in its high efficiency zones with a minimum ON/OFF cycle, leading to efficiency and lifetime enhancement of FC system. Battery SOC have to be kept at a high level during SGV operation, to support the FC during SGV acceleration. In order to improve the SGV’s overall autonomy, it is also important to minimize the stop and go and rotational SGV motion with appropriate acceleration and deceleration rate. Full article

(This article belongs to the Special Issue Electric Vehicle Efficient Power and Propulsion Systems)

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14 pages, 5733 KiB

Open AccessArticle

Switching Frequency Determination of SiC-Inverter for High Efficiency Propulsion System of Railway Vehicle

by Joon-Hyoung Ryu, June-Hee Lee and June-Seok Lee

Energies 2020, 13(19), 5035; https://0-doi-org.brum.beds.ac.uk/10.3390/en13195035 - 24 Sep 2020

Cited by 1 | Viewed by 3514

Abstract

This paper suggests the reasonable switching frequency determination method for achieving highest efficiency of the railway propulsion system consisting the silicon carbide (SiC) inverter and permanent magnet synchronous motor (PMSM). The SiC power device allows increasing the switching frequency of the inverter because it has the small switching power loss. The total efficiency is taken into account for determining the switching frequency of SiC inverter in this paper. In the efficiency analysis of SiC inverter and PMSM, the PMSM drive control is considered with the hybrid switching method combined the synchronous PWM and asynchronous PWM. The result of the analysis shows the efficiency curve of propulsion system depending on the switching frequency. The switching frequency having the minimum power loss of propulsion system is selected based on the extracted power loss curve. Full article

(This article belongs to the Special Issue Electric Vehicle Efficient Power and Propulsion Systems)

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14 pages, 1586 KiB

Open AccessArticle

Adaptive Square-Root Unscented Kalman Filter-Based State-of-Charge Estimation for Lithium-Ion Batteries with Model Parameter Online Identification

by Quan Ouyang, Rui Ma, Zhaoxiang Wu, Guotuan Xu and Zhisheng Wang

Energies 2020, 13(18), 4968; https://0-doi-org.brum.beds.ac.uk/10.3390/en13184968 - 22 Sep 2020

Cited by 33 | Viewed by 2585

Abstract

The state-of-charge (SOC) is a fundamental indicator representing the remaining capacity of lithium-ion batteries, which plays an important role in the battery’s optimized operation. In this paper, the model-based SOC estimation strategy is studied for batteries. However, the battery’s model parameters need to be extracted through cumbersome prior experiments. To remedy such deficiency, a recursive least squares (RLS) algorithm is utilized for model parameter online identification, and an adaptive square-root unscented Kalman filter (SRUKF) is designed to estimate the battery’s SOC. As demonstrated in extensive experimental results, the designed adaptive SRUKF combined with RLS-based model identification is a promising SOC estimation approach. Compared with other commonly used Kalman filter-based methods, the proposed algorithm has higher precision in the SOC estimation. Full article

(This article belongs to the Special Issue Electric Vehicle Efficient Power and Propulsion Systems)

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24 pages, 5407 KiB

Open AccessArticle

On the Comparison of 2- and 4-Wheel-Drive Electric Vehicle Layouts with Central Motors and Single- and 2-Speed Transmission Systems

by Stefano De Pinto, Pablo Camocardi, Christoforos Chatzikomis, Aldo Sorniotti, Francesco Bottiglione, Giacomo Mantriota and Pietro Perlo

Energies 2020, 13(13), 3328; https://0-doi-org.brum.beds.ac.uk/10.3390/en13133328 - 30 Jun 2020

Cited by 25 | Viewed by 7733

Abstract

Electric vehicles (EVs) are characterized by a significant variety of possible powertrain configurations, ranging from one to four electric machines, which can have an on-board or in-wheel layout. Multiple models of production EVs have recently been introduced on the market, with 4-wheel-drive (4WD) architectures based on a central motor within each axle, connected to the wheels through a gearbox, a differential, and half-shafts. In parallel, an important body of research and industrial demonstrations have covered the topic of 2-speed transmission systems for EVs, with the target of enhancing longitudinal acceleration and gradeability performance, while increasing the operating efficiency of the electric powertrain. Although several recent studies compare different electric powertrain architectures, to the best of the authors’ knowledge the literature misses a comparison between 2-wheel-drive (2WD) and 4WD configurations for the same EV, from the viewpoint of drivability and energy consumption. This paper targets this gap, by assessing 2WD and 4WD powertrain layouts with central motors, for a case study light passenger car for urban mobility, including consideration of the effect of single- and 2-speed transmission systems. An optimization routine is used to calculate the energy-efficient gear state and/or torque distribution for each considered configuration. For the specific EV, the results highlight the favourable trade-off of the single-speed 4WD layout, capable of reducing the energy consumption during driving cycles by approximately 9% with respect to the conventional 2WD layout with single-speed transmission, while providing satisfactory drivability and good gradeability, especially in low tire–road friction conditions. Full article

(This article belongs to the Special Issue Electric Vehicle Efficient Power and Propulsion Systems)

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