This paper presents a detailed literature review on switched reluctance motor (SRM) and drive systems in electric vehicle (EV) powertrains. SRMs have received increasing attention for EV applications owing to their reliable structure, fault tolerance ability and magnet free design. The main drawbacks of the SRM are torque ripple, low power density, low power factor and small extended speed range. Recent research shows that multi-stack conventional switched reluctance motors (MSCSRM) and multi-stack switched reluctance motors with a segmental rotor (MSSRM-SR) are promising alternative solutions to reduce torque ripples, increase torque density and increase power factor. Different winding configurations such as single-layer concentrated winding (SLC), single layer mutually coupled winding (SLMC), double layer concentrated winding (DLC), double layer mutually coupled winding (DLMC) and fully-pitched winding (FP) are introduced in the literature in recent years to increase average torque and to decrease torque ripples. This research analyzes winding methods and structure of the SRMs, including conventional and segmental rotors. They have been compared and assessed in detail evaluation of torque ripple reduction, torque/power density increase, noise/vibration characteristics and mechanical structure. In addition, various drive systems are fully addressed for the SRMs, including conventional drives, soft-switching drives, drives with standard inverters and drives with an integrated battery charger. In this paper, the SRM control methods are also reviewed and classified. These control methods include strategies of torque ripple reduction, fault-diagnosis, fault-tolerance techniques and sensorless control. The key contributions of this paper provide a useful basis for detailed analysis of modeling and electromechanical design, drive systems, and control techniques of the SRMs for EV applications.

Recently, wireless power transfer (WPT) systems have been used as battery chargers for electric vehicles. In a WPT system, the design approach and control strategy have a significant impact on the performance of the wireless power transfer systems in electric vehicle powertrains in terms of efficiency, charging power, charging modes, charging time, etc. A characteristic of different topologies appears depending on whether the compensation capacitor is connected in series or parallel with coils. Therefore, it is necessary to select a suitable compensation topology depending on different applications. Thus, this paper proposes a new design methodology and control system for bidirectional 3.7 kW and 7.7 kW WPTs in light-duty electric vehicles (EVs) operating at both 40 kHz and 85 kHz resonance frequencies. In this paper, the series-series (SS) WPT compensation topology is optimally designed and controlled for grid-to-vehicle (G2V) mode using MATLAB/Simulink. A simulation study is performed for a selected WPT design for G2V mode to ensure its functionality and performance at different power levels. Moreover, the magnetic design of the coils and its parameters are verified by using COMSOL. Finally, experimental results are validated for the WPT system.

Automotive Original Equipment Manufacturers (OEMs) require varying levels of functionalities and model details at different phases of the electric vehicles (EV) development process, with a trade-off between accuracy and execution time. This article proposes a scalable modelling approach depending on the multi-objective targets between model functionalities, accuracy and execution time. In this article, four different fidelity levels of modelling approaches are described based on the model functionalities, accuracy and execution time. The highest error observed between the low fidelity (LoFi) map-based model and the high fidelity (HiFi) physics-based model is 5.04%; while, the simulation time of the LoFi model is ~10 ⁴ times faster than corresponding one of the HiFi model. A detailed comparison of all characteristics between multi-fidelity models is demonstrated in this paper. Furthermore, a dSPACE SCALEXIO Hardware-in-the-Loop (HiL) testbench, equipped with a minimal latency of $18\mu $ sec, is used for real-time (RT) model implementation of the EV’s HV DC/DC converter. The performance of the entire HiL setup is compared with the Model-in-the-Loop (MiL) setup and the highest RMSE is limited to 0.54 among the HiL and MiL results. Moreover, the accuracy (95.7%) of the passive component loss estimation is verified through the Finite Element Method (FEM) software model. Finally, the experimental results of a full-scale 30-kW SiC DC/DC converter prototype are presented to validate the accuracy and correlation between multi-fidelity models. It has been observed that the efficiency deviation between the hardware prototype and multi-fidelity models is less than 1.25% at full load. Furthermore, the SiC Interleaved Bidirectional Converter (IBC) prototype achieves a high efficiency of 98.4% at rated load condition.

DC/DC Multiport Converters (MPC) are gaining interest in the hybrid electric drivetrains (i.e., vehicles or machines), where multiple sources are combined to enhance their capabilities and performances in terms of efficiency, integrated design and reliability. This hybridization will lead to more complexity and high development/design time. Therefore, a proper design approach is needed to optimize the design of the MPC as well as its performance and to reduce development time. In this research article, a new design methodology based on a Multi-Objective Genetic Algorithm (MOGA) for non-isolated interleaved MPCs is developed to minimize the weight, losses and input current ripples that have a significant impact on the lifetime of the energy sources. The inductor parameters obtained from the optimization framework is verified by the Finite Element Method (FEM) COMSOL software, which shows that inductor weight of optimized design is lower than that of the conventional design. The comparison of input current ripples and losses distribution between optimized and conventional designs are also analyzed in detailed, which validates the perspective of the proposed optimization method, taking into account emerging technologies such as wide bandgap semiconductors (SiC, GaN).

In this article, a switched reluctance machine (SRM) with six phases and a misaligned segmental rotor is proposed. The segmental rotor has an internal 15-degree misalignment, allowing the SRM structure to be a one-layer 2D structure with a short flux path structure. The proposed SRM produces a relatively low torque ripple by exciting two phases simultaneously. Additionally, an optimization method is applied, allowing for the maximum torque position of one phase to be aligned with the zero-torque position of the adjacent phase. The finite element method (FEM) is used to analyze and design the proposed SRM and to simulate the proposed liquid cooling system. The static torque waveforms are analyzed, and the dynamic torque waveforms are simulated with a drive using SiC MOSFETs. Finally, a prototype is manufactured, and the experiment is performed to validate the design and simulation results.

This article proposes a holistic codesign optimization framework (COF) to simultaneously optimize a power conversion stage and a controller stage using a dual-loop control scheme for multiphase SiC-based DC/DC converters. In this study, the power conversion stage adopts a non-isolated interleaved boost converter (IBC). Besides, the dual-loop control scheme uses type-III controllers for both inner- and outer- loops to regulate the output voltage of the IBC and tackle its non-minimum phase issue. Based on the converter architecture, a multi-objective optimization (MOO) problem including four objective functions (OFs) is properly formulated for the COF. To this end, total input current ripple, total weight of inductors and total power losses are selected as three OFs for the power conversion stage whilst one OF called integral of time-weighted absolute error is considered for the controller stage. The OFs are expressed in analytical forms. To solve the MOO problem, the COF utilizes a non-dominated sorted genetic algorithm (NSGA-II) in combination with an automatic decision-making algorithm to obtain the optimal design solution including the number of phases, switching frequency, inductor size, and the control parameters of type-III controllers. Furthermore, compared to the conventional ‘k-factor’ based controller, the optimal controller exhibits better dynamic responses in terms of undershoot/overshoot and settling time for the output voltage under load disturbances. Moreover, a liquid-cooled SiC-based converter is prototyped and its optimal controller is implemented digitally in dSPACE MicroLabBox. Finally, the experimental results with static and dynamic tests are presented to validate the outcomes of the proposed COF.