Vehicles, Volume 2, Issue 2 (June 2020) – 8 articles

In order to achieve the European Commission’s ambitious climate targets by 2030, BEVs (Battery Electric Vehicles) manufacturers are faced with the challenge of producing more efficient and ecological products. The electromechanical powertrain plays a key role in the efficiency of BEVs, which is why the design parameters in the development phase of electromechanical powertrains must be chosen carefully. One of the central design parameters is the maximum speed of the electric machines and the gear ratio of the connected transmissions. Due to the relationship between speed and torque, it is possible to design more compact and lighter electric machines by increasing the speed at constant power. However, with higher speed of the electric machines, a higher gear ratio is required, which results in a larger and heavier transmission. This study therefore examines the influence of maximum speed on the power density of electromechanical powertrains. Electric machines and transmissions with different maximum speeds are designed with the state-of-the-art for a selected reference vehicle. The designs are then examined with regard to the power density of the overall powertrain system. Compared to the reference vehicle, the results of the study show a considerable potential for increasing the power density of electromechanical powertrains by increasing the maximum speed of the electric machines. Full article

Vehicle regulations include limits for non-volatile particle number emissions with sizes larger than 23 nm. The measurements are conducted with systems that remove the volatile particles by means of dilution and heating. Recently, the option of measuring from 10 nm was included in the Global Technical Regulation (GTR 15) as an additional option to the current >23 nm methodology. In order to avoid artefacts, i.e., measuring volatile particles that have nucleated downstream of the evaporation tube, a heated oxidation catalyst (i.e., catalytic stripper) is required. This review summarizes the studies with laboratory aerosols that assessed the volatile removal efficiency of evaporation tube and catalytic stripper-based systems using hydrocarbons, sulfuric acid, mixture of them, and ammonium sulfate. Special emphasis was given to distinguish between artefacts that happened in the 10–23 nm range or below. Furthermore, studies with vehicles’ aerosols that reported artefacts were collected to estimate critical concentration levels of volatiles. Maximum expected levels of volatiles for mopeds, motorcycles, light-duty and heavy-duty vehicles were also summarized. Both laboratory and vehicle studies confirmed the superiority of catalytic strippers in avoiding artefacts. Open issues that need attention are the sulfur storage capacity and the standardization of technical requirements for catalytic strippers. Full article

With the fast-paced growth of computational horsepower and its affordability, computational fluid dynamics (CFD) has been rapidly evolving as a popular and effective tool for aerodynamic design and analysis in the automotive industry. In the real world, a road vehicle is subject to varying wind and operating conditions that affect its aerodynamic characteristics, and are difficult to reproduce in a traditional wind tunnel. CFD has the potential of becoming a cost-effective way of achieving this, through the application of different boundary conditions. Additionally, one can view wind tunnel testing, be it a fixed-floor or rolling road tunnel, as a physical simulation of actual on-road driving. The use of on-road track testing, and static-floor, and rolling-road wind tunnel measurements are common practices in industry. Subsequently, we investigated the influences of these test conditions and the related boundary conditions on the predictions of the aerodynamic characteristics of the flow field around a vehicle using CFD. A detailed full-scale model of Hyundai Veloster with two vehicle configurations, one with the original and the other with an improved spoiler, were tested using a commercial CFD code STAR-CCM+ from Siemens. Both vehicle configurations were simulated using four different test conditions, providing overall eight different sets of simulation settings. The CFD methodology was validated with experimental data from the Hyundai Aero-acoustic Wind Tunnel (HAWT), by accurately reproducing the test section with static floor boundary conditions. In order to investigate the effect of the blockage ratio on the aerodynamic predictions, the vehicle models were then tested with moving ground plus rotating wheel boundary conditions, using a total of four virtual wind tunnel configurations, with tunnel solid blockage ratios ranging from 1.25%, which corresponds to the actual HAWT, to 0.04%, which presents an open air driving condition. Full article

With the increase of vehicles in large urban centers, there is also an increase in the number of traffic jams and accidents on public roads. The development of a proper Intelligent Transport System (ITS) could help to alleviate these problems by assisting the drivers on route selections to avoid the most congested road sections. Therefore, to improve on this issue, this work proposes an architecture to aid an ITS to detect, analyze, and classify the traffic flow conditions in real time. This architecture also provides a control room dashboard to visualize the information and notify the users about the live traffic conditions. To this end, the proposed solution takes advantage of computer vision concepts to extract the maximum information about the roads to better assess and keep the drivers posted about the traffic conditions on selected highways. The main contribution of the proposed architecture is to perform the detection and classification of the flow of vehicles regardless of the luminosity conditions. In order to evaluate the efficiency of the proposed solution, a testbed was designed. The obtained results show that the accuracy of the traffic classification rate is up to 90% in daylight environments and up to 70% in low light environments when compared with the related literature. Full article

With the development of new energy vehicles, the NVH (Noise, Vibration, Harshness) performance of the permanent magnet synchronous motors (PMSM) for vehicles has attracted more and more attention. The rotor slotting optimization analysis is the critical issue in the NVH performance study of PMSM. In this paper, the theoretical formula of the PMSM radial electromagnetic force is presented. Based on which, the spatial order and frequency order characteristics of the radial force of a 6-pole 36-slot PMSM are analyzed. Firstly, electromagnetic simulation of the motor is carried out, and the specific force components, which may cause an NVH problem, is extracted. Secondly, the harmonics are calculated with a method of freezing the relative magnetic permeability. Thirdly, the motor is optimized by rotor slotting to reduce the amplitudes of these harmonics, and the effect on electromagnetic noise is analyzed in theory and simulation. Finally, the NVH test in original state and after rotor slotting state was performed in the semi-anechoic chamber. The accuracy of the theory and simulation was verified based on the comparison of the measured noise data. This paper provides a new NVH optimization idea, this method can quickly locate the fundamental problem location of electromagnetic NVH, provide a fast channel for electromagnetic NVH optimization from simulation to verification, and improve the optimization efficiency of NVH. Full article

This paper presents a novel framework to enable automatic re-training of the supervisory powertrain control strategy for hybrid electric vehicles using supervised machine learning. The aim of re-training is to customize the control strategy to a user-specific driving behavior without human intervention. The framework is designed to update the control strategy at the end of a driving task. A combination of dynamic programming and supervised machine learning is used to train the control strategy. The trained control strategy denoted as SML is compared to an online-implementable strategy based on the combination of the optimal operation line and Pontryagin’s minimum principle denoted as OOL-PMP, on the basis of fuel consumption. SML consistently performed better than OOL-PMP, evaluated over five standard drive cycles. The EUDC performance was almost identical while on FTP75 the OOL-PMP consumed 14.7% more fuel than SML. Moreover, the deviation from the global benchmark obtained from dynamic programming was between 1.8% and 5.4% for SML and between 5.8% and 16.8% for OOL-PMP. Furthermore, a test-case was conducted to emulate a real-world driving scenario wherein a trained controller is exposed to a new drive cycle. It is found that the performance on the new drive cycle deviates significantly from the optimal policy; however, this performance gap is bridged with a single re-training episode for the respective test-case. Full article

Of all driving functions, one of the critical maneuvers is the lane merge. A cooperative Nonlinear Model Predictive Control (NMPC)-based optimization method for implementing a highway lane merge of two connected autonomous vehicles is presented using solutions obtained by the direct multiple shooting method. A performance criteria cost function, which is a function of the states and inputs of the system, was optimized subject to nonlinear model and maneuver constraints. An optimal formulation was developed and then solved on a receding horizon using direct multiple shooting solutions; this is implemented using an open-source ACADO code. Numerical simulation results were performed in a real-case scenario. The results indicate that the implementation of such a controller is possible in real time, in different highway merge situations. Full article

In order to improve the fuel economy of vehicles, based on the automated mechanical transmission (AMT), a plug-in hybrid electric vehicle (PHEV) hybrid transmission for low-end multi-purpose vehicles (MPVs) is developed. To obtain the statistics of the best-selling models, we took several best-selling models in the Chinese market as the research object to study the relationship between power demand, energy demand, weight, and cost. The power requirements and energy requirements of PHEVs are decoupled. According to the decoupled theory, a single-motor parallel scheme based on the AMT is adopted to develop a PHEV hybrid transmission. In the distribution of engine and motor power, the engine just needs to meet the vehicle’s constant driving power, and the backup power can be provided by the motor, which means we can use an engine with a smaller power rating. The energy of short-distance travel is mainly provided by the motor, which can make full use of the battery, reducing the fuel consumption. The energy of long-distance travel is mainly provided by the engine, which can reduce the need for battery capacity. The working modes of the electrified mechanical transmission (EMT) are proposed, using P3 as the basic working mode and setting the P2 mode at the same time, and the gear ratios are designed. Based on the above basic scheme, two rounds of prototype development and assembling prototype vehicles for testing are carried out for the front-engine-front-drive (FF) layout. The test results show that the vehicle’s economy has been improved compared to the unmodified vehicle, and the fuel-saving rate of 100 kilometers has been achieved at 35.18%. The prototype development and the vehicle matching verify the effectiveness of the new configuration based on AMT. Full article