World Electr. Veh. J., Volume 12, Issue 4 (December 2021) – 108 articles

The effectiveness of inductive power transfer (IPT) presents a serious challenge for improving the global recharge system performance. An electric vehicle (EVs) needs to be charged rapidly and have maximum power when it is charged with wireless technology. Based on various research, the performance of this recharge system is attached to several points and the frequency resonance is one of those parameters that can influence. In this paper, we try to explore the relationship between the obtained power and the signal input frequency for charging a lithium battery, solve the class imbalance problem and understand the maximum allowed frequency. To obtain the results, a mathematical model was first created to demonstrate the relationship, then the dynamic model was validated and tested using the Matlab Simulink platform. The performance of the worldwide wireless recharging system in terms of frequency variation is depicted in a summary graph. Full article

In order to improve the position tracking precision of dual permanent magnet synchronous motor (PMSM) systems, a unified nonlinear predictive control (UNPC) strategy based on the unified modeling of two PMSM systems is proposed in this paper. Firstly, establishing a unified nonlinear model of the dual-PMSM system, which contains uncertain disturbances caused by parameters mismatch and external load changes. Then, the position contour error and tracking errors are regarded as the performance index inserted into the cost function, and the single-loop controller is obtained by optimizing the cost function. Meanwhile, the nonlinear disturbance observer is designed to estimate the uncertain disturbances, which is used for feed-forward compensation control. Finally, the proposed strategy is experimentally validated on two 2.3 kW permanent magnet synchronous motors, and the experimental results show that effectiveness and feasibility of proposed strategy. Full article

If an accident occurs during charging of an electric vehicle (EV), it will cause serious damage to the car, the person and the charging facility. Therefore, this paper proposes a fault warning method for an EV charging process based on an adaptive deep belief network (ADBN). The method uses Nesterov-accelerated adaptive moment estimation (NAdam) to optimize the training process of a deep belief network (DBN), and uses the historical data of EV charging to construct the ADBN of the normal charging process of an EV model. The real-time data of EV charging is obtained and input into the constructed ADBN model to predict the output, calculate the Pearson coefficient between the predicted output and the actual measured value, and judge whether there is a fault according to the size of the Pearson coefficient to realize the fault warning of the EV charging process. The experimental results show that the method is not only able to accurately warn of a fault in the EV charging process, but also has higher warning accuracy compared with the back propagation neural network (BPNN) and conventional DBN methods. Full article

Recent United Nations high-level dialogue on energy, which had emphasized on energy usage and environmental protection, has renewed commitments by different countries on the adoption of electric vehicle (EVs). This paper aims to analyze the economic feasibility of establishing electrical charging stations, which is an important factor for the wide adoption of EVs, using life cycle cost analysis. Although local data have been used, the method can be easily adopted to analyze economic feasibility at different markets. The findings have revealed that an electrical charging station is only feasible when the acquisition cost is kept to a minimum to return 1.47 times the initial investment in terms of life cycle cost. An acquisition cost of BND 29,725 on the electrical charging station represents the threshold below which an electrical charging station is more attractive. In order to promote these charging stations, the government needs to provide multiple incentives, including a subsidy to reduce the acquisition cost, relaxing control on the electric selling price, taxing the establishment of conventional filling stations, and minimally reducing the profit margin on the selling price of fossil fuel. It has been shown that a 40% initial subsidy on the purchase of electrical charging stations, coupled with a slight subsidy of BND 0.018/kWh on electricity, would make electrical charging stations economically competitive. To reach its target of 60% electrification of the transportation sector, Brunei would need to implement a structure program to establish between 646 and 3300 electrical charging stations by the year 2035, to cater for its expected number of EVs. Full article

The electrification of the transportation sector will increase the demand for electric power, potentially impacting the peak load and power system operations. A change such as this will be multifaceted. A power system production cost model (PCM) is a useful tool with which to analyze one of these facets, the operation of the power system. A PCM is a computer simulation that mimics power system operation, i.e., unit commitment, economic dispatch, reserves, etc. To understand how electric vehicles (EVs) will affect power system operation, it is necessary to create models that describe how EVs interact with power system operations that are suitable for use in a PCM. In this work, EV charging data from the EV Project, reported by the Idaho National Laboratory, were used to create scalable, statistical models of EV charging load profiles suitable for incorporation into a PCM. Models of EV loads were created for uncoordinated and coordinated charging. Uncoordinated charging load represents the load resulting from EV owners that charge at times of their choosing. To create an uncoordinated charging load profile, the parameters of importance are the number of vehicles, charger type, battery capacity, availability for charging, and battery beginning and ending states of charge. Coordinated charging is where EVs are charged via an “aggregator” that interacts with a power system operator to schedule EV charging at times that either minimize system operating costs, decrease EV charging costs, or both, while meeting the daily EV charging requirements subject to the EV owners’ charging constraints. Beta distributions were found to be the most appropriate distribution for statistically modeling the initial and final state of charge (SoC) of vehicles in an EV fleet. A Monte Carlo technique was implemented by sampling the charging parameters of importance to create an uncoordinated charging load time series. Coordinated charging was modeled as a controllable load within the PCM to represent the influence of the EV fleet on the system’s electricity price. The charging models were integrated as EV loads in a simple 5-bus system to demonstrate their usefulness. Polaris Systems Optimization’s PCM power system optimizer (PSO) was employed to show the effect of the EVs on one day of operation in the 5-bus power system, yielding interesting and valid results and showing the effectiveness of the charging models. Full article

In order to make up for the shortcomings of independent sensors and provide more reliable estimation, a multi-sensor fusion framework for simultaneous localization and mapping is proposed in this paper. Firstly, the light detection and ranging (LiDAR) point cloud is screened in the front-end processing to eliminate abnormal points and improve the positioning and mapping accuracy. Secondly, for the problem of false detection when the LiDAR is surrounded by repeated structures, the intensity value of the laser point cloud is used as the screening condition to screen out robust visual features with high distance confidence, for the purpose of softening. Then, the initial factor, registration factor, inertial measurement units (IMU) factor and loop factor are inserted into the factor graph. A factor graph optimization algorithm based on a Bayesian tree is used for incremental optimization estimation to realize the data fusion. The algorithm was tested in campus and real road environments. The experimental results show that the proposed algorithm can realize state estimation and map construction with high accuracy and strong robustness. Full article

With the increasing demand of driving range of new energy vehicle (NEV), design optimization for energy efficiency of traction motors became more important. However, traction motor design is complex since multiple objectives should be satisfied, such as the required torque-speed operating range and package and thermal constraints. This dramatically increases the computation time of the design optimization process, while the additional energy efficiency objective of the whole driving cycle. This paper proposes an equivalent driving cycle points extraction method, based on energy consumption equivalence to facilitate the design optimization of traction motors. This paper presents necessary rules of multiobjective optimization methods, and then gives an optimization process and proves the effectiveness. Full article

For the sake of the increasing demand of hydrogen fuel cell vehicles, there are more concerns on the safety of hydrogen refueling stations. As one of the key pieces of equipment, the hydrogen dispenser has drawn attention on this aspect since it involves massive manual operations and may be bothered by a high probability of failure. In this paper, a numerical study is conducted to simulate the possible leakage events of the hydrogen dispenser based on a prototype in China whose working pressure is 70 MPa. The leakage accident is analyzed with respect to leakage sizes, leak directions, and the time to stop the leakage. It is found that, due to the large mass flow rate under such high pressure, the leak direction and the layout of the components inside the dispenser become insignificant, and the ignitable clouds will form inside the dispenser in less than 1 s if there is a leakage of 1% size of the main tube. The ignitable clouds will form near the vent holes outside the dispenser, which may dissipate quickly if the leakage is stopped. On the other hand, the gas inside the dispenser will remain ignitable for a long time, which asks for a design with no possible ignition source inside. The results can be useful in optimizing the design of the dispenser, regarding the reaction time and sensitivity requirements of the leakage detector, the size and amount of vent holes, etc. Full article

As the electrification of the transportation sector advances, fleet operators have to rethink their approach regarding fleet management against the background of limiting factors, such as a reduced range or extended recharging times. Charging infrastructure plays a critical role, and it is worthwhile to consider its planning as an integral part for the long-term operation of an electric vehicle fleet. In the category of fixed route transportation systems, the predictable character of the routes can be exploited when planning charging infrastructure. After a prior categorization of stakeholders and their respective optimization objectives in the sector coupling domain, a cost optimization framework for fixed route transportation systems is presented as the main contribution of this work. We confirm previous literature in that there is no one-fits-all optimization method for this kind of problem. The method is tested on seven scenarios for the public transport operator of Darmstadt, Germany. The core optimization is formulated as a mixed integer linear programming (MILP) problem. All scenarios are terminated by the criterion of a maximum solving time of 48 h and provide feasible solutions with a relative MIP-gap between 7 and 24%. Full article

Demand for pure electric vehicles has been found to be increasing over the years. This has necessitated the development of a model that would serve as a predicting machine for manufacturing different types of pure electric vehicles. Direct Artificial Neural Network approach was used for predictions of nine different parameters commonly found in pure electric cars. Predictions were found to be of high degree of accuracy while using unit and overall model errors as the basis of performance measurement. The mean absolute error, mean square error and root mean square error of the model were 0.109, 0.218 and 0.467, respectively, when the combined electric charge consumption was used for modeling. For the model formation, using the same variable, the losses for the training and testing were 3.9132 × 10⁻⁶ and 9.698 × 10⁻⁷, respectively. The model was also evaluated using redefined datasets. The developed model can be used by manufacturers and engineers to simulate future designs when certain parameters are given. Full article

Accurate capacity estimation can ensure the safe and reliable operation of lithium-ion batteries in practical applications. Recently, deep learning-based capacity estimation methods have demonstrated impressive advances. However, such methods suffer from limited labeled data for training, i.e., the capacity ground-truth of lithium-ion batteries. A capacity estimation method is proposed based on a semi-supervised convolutional neural network (SS-CNN). This method can automatically extract features from battery partial-charge information for capacity estimation. Furthermore, a semi-supervised training strategy is developed to take advantage of the extra unlabeled sample, which can improve the generalization of the model and the accuracy of capacity estimation even in the presence of limited labeled data. Compared with artificial neural networks and convolutional neural networks, the proposed method is demonstrated to improve capacity estimation accuracy. Full article

To solve the problem of water management subsystem fault diagnosis in a proton exchange membrane fuel cell (PEMFC) system, a novel approach based on learning vector quantization neural network (LVQNN) and kernel principal component analysis (KPCA) is proposed. In the proposed approach, the KPCA method is used for processing strongly coupled fault data with a high dimension to reduce the data dimension and to extract new low-dimensional fault feature data. The LVQNN method is used to carry out fault recognition using the fault feature data. The effectiveness of the proposed fault detection method is validated using the experimental data of the PEMFC power system. Results show that the proposed method can quickly and accurately diagnose the three health states: normal state, water flooding failure and membrane dry failure, and the recognition accuracy can reach 96.93%. Therefore, the method proposed in this paper is suitable for processing the fault data with a high dimension and abundant quantities, and provides a reference for the application of water management subsystem fault diagnosis of PEMFC. Full article

To conserve rare earth resources, consequent-pole permanent-magnet (CPPM) machine has been studied, which employs iron-pole to replace half PM poles. Meanwhile, to increase flux-weakening ability, hybrid excitation CPPM machine with three-dimensional (3-D) flux flow has been proposed. Considering finite element method (FEM) is time-consuming, for the analysis of the CPPM machine, this paper presents a nonlinear varying-network magnetic circuit (NVNMC), which can analytically calculate the corresponding electromagnetic performances. The key is to separate the model of CPPM machine into different elements reasonably; thus, the reluctances and magnetomotive force (MMF) sources in each element can be deduced. While taking into account magnetic saturation in the iron region, the proposed NVNMC method can accurately predict the 3-D magnetic field distribution, hence determining the corresponding back-electromotive force and electromagnetic power. Apart from providing fast calculation, this analytical method can provide physical insight on how to optimize the design parameters of this CPPM machine. Finally, the accuracy of the proposed model is verified by comparing the analytical results with the results obtained by using FEM. As a result, with so many desired attributes, this method can be employed for machine initial optimization to achieve higher power density. Full article

To satisfy the high-rate power demand fluctuations in the complicated driving cycle, electric vehicle (EV) energy storage systems should have both high power density and high energy density. In order to obtain better energy and power performances, a combination of battery and supercapacitor are utilized in this work to form a semi-active hybrid energy storage system (HESS). A parameter matching method of battery-supercapacitor HESS for electric vehicles (EVs) is proposed. This method can meet the performance indicators of EVs in terms of power and energy for parameter matching. The result shows that optimized parameter matching is obtained by reducing the weight and cost. Full article

An increment of magnetic field strength inevitably appears at the shield edge if a magnetic shield is made of a soft magnetic material, and that increment becomes more serious if this shield is combined with the chassis of an electrical vehicle (EV). This phenomenon is caused by the fringe effect, which limits the transfer efficiency of the coupler for the wireless power transmission (WPT) systems of EV. This phenomenon, and its relationships with some parameters, are analyzed in this paper, and these relationships are fitted to estimate the increment for different shield structures. A magnetic shield structure to reduce the increment of the magnetic field strength and improve coupler efficiency is herein proposed. The effectiveness and correctness of the fitting curves and the advantages of the proposed shield structure are demonstrated by finite element analyses results. Full article

A patent pool strategy was proposed for use in the electric vehicle cell industry to manage patent licensing disputes and litigation. How to promote EV cell innovation diffusion under a patent pool scenario is unclear. We introduced an innovation diffusion channel model comprising different players with patent licensing relationships and market competition relationships following evolutionary game analysis and simulation. We found the interlinked factors that influenced evolutionary stable strategies with a sensitivity test on all factors to identify the important and unimportant factors. To achieve the maximum return for the players, an optimization algorithm was introduced to find the maximum weighted object function. The decision and policy makers could focus on important factors such as improving the technology’s competitive advantages, delivering more profits to its licensees with reasonable licensing fees, and finding the best patent pool strategy with the support of the optimization algorithm to balance the competition relationships and patent licensing relationships between players. Full article

Aiming at the complex experimental conditions of multi-physical field coupling in the analysis of thermal characteristics of lithium-ion batteries, a three-dimensional electrochemical-thermal flow coupling model for lithium-ion batteries was established using COMSOL Multiphysics software. Through the analysis of simulation results, the thermal characteristics of lithium-ion batteries for electric vehicles were explored from the aspects of heat generation and dissipation. It was found that increasing the charge–discharge rate and the electrode thickness will increase the temperature rise rate of lithium-ion batteries, and the temperature rise rate of lithium-ion batteries is the highest during their first time charging and discharging. Increasing the airflow velocity and reducing the size of the inlet flow area can improve the cooling effect on the cell. Under a single inlet, the cooling effect of the airflow field entering from the negative electrode is better than that from the positive electrode. Full article

This article uses the NMNL (nested multinominal logit) model to analyze the impact of different policies on the cost of owning a vehicle by a consumer and discusses the changes in the share of various fuel-driven types of passenger vehicles that may be brought by different policy portfolios. This article also considers the differences in the development of various technical routes, conducts the nested classification calculation of different models, divides the differences in product preferences and obtains the market share results that are more in line with the market development status, providing a basis for the formulation of policies related to new energy vehicles. The study found that the popularization of NEVs requires more cost-reducing measures. As policies that consumers can perceive, consumers are more sensitive to fiscal and taxation policies than other types of policies. Based on the calculation of policy effects, this article recommends a policy plan to gradually impose vehicle purchase tax on NEVs after 2024, increase the fuel tax rate in stages after 2025, and impose an excise tax on BEVs and FCEVs after 2030. The plan can guarantee the stability of support for NEVs and the gradual reduction of financial investment. Full article

The permanent magnet synchronous motor (PMSM) is used widely in electric vehicle application due to its high-power density and efficiency. Stator fault is a frequently fault in the motor as it usually works in a harsh environment. Therefore, a stator fault diagnosis method based on the offline motor parameter measurement is proposed to detect and evaluate the stator fault in this paper. Firstly, the line-to-line resistance and inductance of a healthy motor are analyzed when a DC voltage and a high-frequency voltage are excited to the motor respectively, where the DC and AC equivalent circuits at a standstill are introduced. Then, to analyze the resistance and inductance of the stator fault, an extra branch is added to the fault part to obtain the fault equivalent circuits. Accordingly, the stator fault resistance and inductance are derived, and then the resistance and inductance differences between healthy and fault motors are analyzed to provide the basis for the stator fault detection. Furthermore, the fault indicators are defined based on the resistance and inductance differences when a motor has a stator fault. Hence the stator fault severity and location can be evaluated by using these fault indicators. Finally, the experimental results from a 400 W permanent magnet synchronous motor are demonstrated to validate the proposed method. Full article

In this study, gradient boosting decision tree (GBDT) and ordinary least squares (OLS) models were constructed to systematically ascertain the influencing factors and electric vehicle (EV) use action laws from the perspective of travelers. The use intensity of EVs was represented by electric vehicle miles traveled (eVMT); variables such as the charging time, travel preference, and annual income were used to describe the travel characteristics. Seven variables, including distance to the nearest business district, road density, public transport service level, and land use mix were extracted from different dimensions to describe the built environment, explore the influence of the travel behavior mode and built environment on EV use. From the eVMT survey data, points of interest (POI) data, urban road network data, and other heterogeneous data from Chongqing, an empirical analysis of EV usage intensity was conducted. The results indicated that the deviation of the GBDT model (9.62%) was 11.72% lower than that of the OLS model (21.34%). The charging time was the most significant factor influencing the service intensity of EVs (18.37%). The charging pile density (15.24%), EV preference (11.52%), and distance to the nearest business district (10.28%) also exerted a significant influence. Full article

This study aimed to determine and analyze the performance of an electric motor installed in a small city car, which was an internal combustion engine (ICE) car with manual transmission and front-wheel drive converted into an electric vehicle. A manual transmission vehicle was used, considering its type is the cheapest. This was to push aside the perception that electric cars are not accessible to the lower classes. Another technical matter was the focus on the power and torque performance of the electric motor and the transmission. A 7.5 KW three-phase induction motor was installed and assembled with 200 AH 76.8 VDC batteries. Electronic power steering (EPS) and the air conditioner (AC) were not operated, while power for the electrical accessories and power analyzer was obtained from a separate 12 VDC battery. Vehicle analysis focused on the power consumption, which was measured and acquired using a power analyzer. The vehicle was driven in real terms with three passengers. GPS was also used to determine the vehicle position and collect elevation data during testing. The derivatives of the GPS data were the speed, acceleration, and distance traveled by the vehicle. The initial hypothesis was that the car could cover a distance of 30 km with regular usage. Full article

In the commercialization process of wireless electric vehicle charging (WEVC), it is essential to ensure the interoperability between diverse WEVC systems due to the wide application of various coil configurations and compensation topologies. This paper proposes a novel electrical interoperability evaluation method based on impedance indices and corresponding feasible space in the complex plane. Firstly, the electromagnetic description of the coil system is introduced to reveal the energy flow process of WEVC system. Further, two key impedance indices and their feasible space are derived and verified. Interoperability evaluation results show that the reference devices in Chinese WEVC standard GB/T 38775.6 and GB/T 38775.7 are able to achieve the requirements of power capability. Moreover, it is necessary to reduce the duty cycle of rectifier when the battery voltage rises so as to narrow down the variation of load resistance and avoid dangerous working conditions. The proposed method can effectively evaluate the electrical interoperability of WEVC systems from different manufacturers under different power or distance levels before conducting experiments. Full article

A reasonable plan for charging stations is critical to the widespread use of electric vehicles. In this paper, we propose an optimal planning method for electric vehicle charging stations. First of all, we put forward a forecasting method for the distribution of electric vehicle fast charging demand in urban areas. Next, a new mathematical model that considers the mutual benefit of electric vehicle users and the power grid is set up, aiming to minimize the social cost of charging stations. Then, the model is solved by the Voronoi diagram combined with improved particle swarm optimization. In the end, the proposed method is applied to an urban area, simulation results demonstrate that the proposed method can yield optimal location and capacity of each charging station. A contrasting case is carried out to verify that improved particle swarm optimization is more effective in finding the global optimal solution than particle swarm optimization. Full article

Electric vehicles (EV) are growing fast in recent years with the widespread concern about carbon neutrality. The development of charging infrastructures needs to be in phase with EV both in terms of quantity and charging time to decrease the range anxiety of EV users and resource waste. This paper proposed a multistage and dynamic layout optimization model based on mixed integer linear programming (MILP) for EV charging stations (CSs) to minimize the total social costs (TSC) consisting of the detour cost of EV users and the construction, relocation, and operating cost of CSs. The charging satisfaction coefficient and M/M/S/K model of queuing theory has been introduced to determine the desirable charging supply. The spatial-temporal distribution of charging demand was modeled based on the behavior analysis of travelers and over the discrete-time intervals for a day. Comparison studies based on the Sioux Falls network reveal that TSC with a multistage optimization strategy will drop 8.79% from that with a one-time optimization strategy. Charging service quality, relocation cost, and road network scales have a significant impact on the optimization results according to the sensitivity analysis. Full article

This paper investigates the win-win commercialization mode of aggregating electric vehicles (EVs) in demand side for ancillary service. We have conducted a half-year-long incentive verification experiment covering 10,066 electric vehicle owners in Beijing. Based on the experimental results, we develop an incentive-based mechanism that enables electric vehicles to participate the wholesale capacity market through an aggregator. The aggregator, which is held by charging service operators can make a profit by designing a smart pricing policy. In this process, not only the electric vehicle owners but also the utility can gain benefits. Full article

An electric road system (ERS) enables transfer of electric energy to a moving vehicle, making it possible to reduce the capacity—and cost—of the battery and the need for static chargers. A conductive electric road allows for relatively low complexity whilst being able to provide high levels of power. When utilising a conductive electric road, safety precautions must be considered with regard to isolation between the charging supply (the electric road) and the vehicle’s traction voltage system (TVS), since no protective Earth connection can be guaranteed. Isolation can be achieved by separating the two systems galvanically or by double isolating the entire TVS and all equipment connected to it on-board the vehicle. This study used the experimental results from a previous paper to model and evaluate three different electric powertrains/charger topologies, including a novel integrated design fulfilling the required safety features. The models were used in a full vehicle model and further investigated in a city bus scenario in terms of how charging performance, energy consumption and battery ageing are affected by the aforementioned charging topologies and electric road characteristic. We discovered that charging topology has a strong influence on energy consumption, and that electric road characteristics have a strong influence on battery ageing. Full article

The emergence of electric vehicles (EV) is inevitable. In Indonesia, EVs in various forms have been introduced to the market. However, the adoption of EV in the Indonesian market is still negligible. The purpose of this paper is to make an early prediction of consumers’ purchase intentions towards EV, particularly battery electric vehicles (BEV), in Indonesia. A multi-criteria decision model based on the analytic network process (ANP) approach has been proposed. There are several main criteria used to explain the purchase/don’t purchase decision towards BEV, namely functionality, emotion, cost of ownership, and car identity. Through a series of pairwise comparisons involving a number of target customers of senior level professionals, their purchase intentions towards BEV have been predicted. The results of this study show that these early wealthy, highly educated consumers have a moderate preference towards purchasing BEV. Their intention to purchase is influenced by criteria as follows: emotion (42.64%), functionality (25.94%), car identity (21.87%), and cost of ownership (9.55%). Even though the invited target customers do not represent the mass market, the findings of this study could help BEV makers in Indonesia choose who the early adopters are and find the BEV product-market fit in order to accelerate the adoption of electric vehicles. Full article

A great many EVs in cold areas suffer from range attenuation in winter, which causes driver anxiety concerning the driving range, representing a hot topic. Many researchers have analyzed the reasons for range attenuation but the coupling mechanism of the battery as well as the vehicle and driving conditions have not been clearly estimated. To quantitatively investigate the driving range attenuation of electric vehicles (EVs) during winter, an EV model mainly integrated with a passenger-cabin thermal model, battery model, and vehicle dynamic model was constructed and simulated based on the mass-produced Wuling HongGuang Mini EV. Real vehicle dynamic driving data was used to validate the model. Based on NEDC driving conditions, the driving range calculation formula and energy flow diagram analysis method were used. The reason for attenuation was evaluated quantitatively. Results show that battery energy loss and breaking recovery energy loss contribute nearly half of the range attenuation, which may be alleviated by battery preheating. Suggestions for extending driving range are proposed based on the research. Full article

The power unit is mainly responsible for the power converter’s function of the electric vehicle, which converts the DC power from the battery to the AC power to drive the motor. Therefore, the parasitic parameters of the power unit will directly affect the output performance of the vehicle. In this paper, the parasitic parameters of the power unit are analyzed. By using an asymmetric design, the capacitor cost and performance are balanced. Moreover, the structure of the busbar is optimized according to the reasonable theoretical analysis. The simulation comparison before and after the optimization, and the comparison results of the measurement results by the double pulse test, are given to verify the optimization. Additionally, the ESL of the busbar is reduced by 10 nH. The results will offer some references to the power unit design. Full article