World Electric Vehicle Journal

21 pages, 4218 KiB

Open AccessArticle

State of Charge Estimation of Lithium-Ion Batteries Based on an Improved Sage-Husa Extended Kalman Filter Algorithm

by Lihong Xiang, Li Cai, Nina Dai, Le Gao, Guoping Lei, Junting Li and Ming Deng

World Electr. Veh. J. 2022, 13(11), 220; https://doi.org/10.3390/wevj13110220 - 21 Nov 2022

Cited by 3 | Viewed by 1909

An improved Sage-Husa extended Kalman filter (SHEKF) algorithm is intended to improve the accuracy and stability of SOC prediction. In this paper, two different exponential weighting algorithms are used to adaptively select the forgetting factor for adaptive noise estimation. Moreover, the OCV-SOC curve [...] Read more.

An improved Sage-Husa extended Kalman filter (SHEKF) algorithm is intended to improve the accuracy and stability of SOC prediction. In this paper, two different exponential weighting algorithms are used to adaptively select the forgetting factor for adaptive noise estimation. Moreover, the OCV-SOC curve is obtained using a 7-segment linear fitting method before the algorithms estimate the SOC. In addition, by combining this improved method with a third-order RC equivalent circuit model in the dynamic stress test (DST) case the convergence time is reduced by 0.15 s compared to the second-order RC equivalent circuit model. Following that, four different types of comparison experiments are carried out by comparing the improved algorithm to EKF and other SHEKF algorithms.The estimation accuracy under DST conditions of 0 °C, 25 °C and 45 °C is approximately 0.5%, 2.2% and 1.3% improvement compared to the EKF algorithm. Full article

(This article belongs to the Special Issue Novel Electric Vehicle Technology towards Low Carbon Future: Advanced Powertrain, Energy Management and Grid Interaction)

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21 pages, 9723 KiB

Open AccessArticle

Model-Based Fault Diagnosis of Actuators in Electronically Controlled Air Suspension System

by Xinwei Jiang, Xing Xu and Haiqiang Shan

World Electr. Veh. J. 2022, 13(11), 219; https://doi.org/10.3390/wevj13110219 - 21 Nov 2022

Cited by 2 | Viewed by 2001

Abstract

The air suspension adjusts the height of the vehicle body through charging and bleeding air to meet the high performance of the vehicle, which needs a reliable electronic control system. Through fault tree analysis of the electronically controlled air suspension (ECAS) system and [...] Read more.

The air suspension adjusts the height of the vehicle body through charging and bleeding air to meet the high performance of the vehicle, which needs a reliable electronic control system. Through fault tree analysis of the electronically controlled air suspension (ECAS) system and considering the correlation between the duty cycle and flow rate of the air spring solenoid valve, the fault model of the solenoid valve is constructed, and the fault diagnosis design method of the ECAS system solenoid valve based on multiple extended Kalman filter banks (EKFs) is proposed. An adaptive threshold is used to realize fault diagnosis, and active fault-tolerant control is carried out based on an analytical model. The real controller based on d2p rapid prototyping technology and the vehicle model based on AMESim are further verified on the hardware-in-the-loop (HiL) simulation test platform and compared with the pure simulation results. The test results show that the fault diagnosis and fault-tolerant control algorithm can work normally in the actual controller, and can effectively realize the fault diagnosis and fault-tolerant control of the actuator in the vehicle ECAS system. Full article

(This article belongs to the Special Issue Advanced X-by-Wire Technologies in Design, Control and Measurement for Vehicular Electrified Chassis)

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13 pages, 3199 KiB

Open AccessArticle

A New Control Strategy for Energy Management of Bidirectional Chargers for Electric Vehicles to Minimize Peak Load in Low-Voltage Grids with PV Generation

by Parnian Fakhrooeian and Volker Pitz

World Electr. Veh. J. 2022, 13(11), 218; https://doi.org/10.3390/wevj13110218 - 19 Nov 2022

Cited by 3 | Viewed by 1672

Abstract

This paper introduces a new bidirectional vehicle-to-grid (V2G) control strategy for energy management of V2G charging points equipped with photovoltaic systems (PVs), considering the interaction between V2G chargers, electric vehicle (EV) owners, and the network operator. The proposed method aims to minimize peak [...] Read more.

This paper introduces a new bidirectional vehicle-to-grid (V2G) control strategy for energy management of V2G charging points equipped with photovoltaic systems (PVs), considering the interaction between V2G chargers, electric vehicle (EV) owners, and the network operator. The proposed method aims to minimize peak load, grid infeed power, feeder loading, and transformer loading by scheduling EVs charging and discharging. The simulation experiments take into account three EV battery capacities as well as two levels of EV penetration. In order to validate the effectiveness of the proposed approach, five scenarios are studied in a single feeder of a low-voltage (LV) distribution network in DIgSILENT PowerFactory, which comprises a combination of residential and commercial loads as well as PV systems. Simulation results demonstrate that the proposed V2G strategy improves the paper’s objectives by providing ancillary services to the grid. Full article

(This article belongs to the Special Issue Charging Infrastructure for EVs)

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18 pages, 6318 KiB

Open AccessArticle

High-Frequency Square Wave Injection Sensorless Control Method of IPMSM Based on Oversampling Scheme

by Zhiqiang Wang, Qi Guo, Jifeng Xiao, Te Liang, Zhichen Lin and Wei Chen

World Electr. Veh. J. 2022, 13(11), 217; https://doi.org/10.3390/wevj13110217 - 18 Nov 2022

Cited by 3 | Viewed by 2870

Abstract

In view of the disadvantages of the traditional high-frequency square wave signal injection method in the low-speed operation of high-power interior permanent magnet synchronous motor (IPMSM), such as the large error of rotor position calculation and delay of position update, a method based [...] Read more.

In view of the disadvantages of the traditional high-frequency square wave signal injection method in the low-speed operation of high-power interior permanent magnet synchronous motor (IPMSM), such as the large error of rotor position calculation and delay of position update, a method based on high-frequency square wave signal injection is proposed to obtain an effective vector action current through oversampling. When the vector is zero, the current changes to not zero, but when the vector is effective, the current changes greatly. In the traditional sampling and calculation methods, the change of the zero-vector is ignored, resulting in errors, especially in the case of small power, and the errors are more obvious. Through the method of oversampling the current of the effective vector, the high-frequency response current of the effective vector is obtained. Through the reasonable demodulation method, the high-frequency response current of the effective vector is extracted, and then the rotor position information is obtained through the phase-locked loop. On this basis, the influence of the inherent nonlinear characteristics of the motor system and the sampling delay on the calculation of the rotor position is analyzed, and the error is compensated to obtain a more accurate rotor position. Full article

(This article belongs to the Special Issue Electrical Machines Design and Control in Electric Vehicles)

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12 pages, 4312 KiB

Open AccessArticle

Performance Simulation of Long-Stator Linear Synchronous Motor for High-Speed Maglev Train under Three-Phase Short-Circuit Fault

by Hongyi Yang, Yanxin Li and Qinfen Lu

World Electr. Veh. J. 2022, 13(11), 216; https://doi.org/10.3390/wevj13110216 - 18 Nov 2022

Cited by 2 | Viewed by 2102

Abstract

The high-speed Maglev train is driven by long-stator linear synchronous motors (LLSM). During the long-time outdoor operation, the insulation material of the armature winding may be damaged, either due to aging or the movement of the windings. This may result in the three-phase [...] Read more.

The high-speed Maglev train is driven by long-stator linear synchronous motors (LLSM). During the long-time outdoor operation, the insulation material of the armature winding may be damaged, either due to aging or the movement of the windings. This may result in the three-phase short-circuit fault, which affects the traction performance and the operation of the train. In this paper, a simulation model of the high-speed Maglev train traction system with a three-phase short-circuit fault LLSM is established, including the converters at two ends, feeder cables, segmented LLSM and traction control system. The system adopts a double-end power supply mode. The model divides the fault segment LLSM into two parts. One part is connected to the converter, which is equivalent to a normal operating segment with shortened long-stator. The other part is equivalent to a three-phase short-circuit linear generator. Based on this model, the influence of running speed and fault segment length on the traction performance of the train is simulated. In addition, the stator current, acceleration and traction force of the Maglev train during fault segment are investigated in the acceleration phase, deceleration phase and constant speed phase, respectively. The results can provide a reference for three-phase short-circuit fault diagnosis. Full article

(This article belongs to the Special Issue Recent Advances in Novel Permanent Magnet and Magnetless Machines and Control for Electric Vehicles)

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13 pages, 16533 KiB

Open AccessArticle

Analysis of DC Winding Induced Voltage in Wound-Rotor Synchronous Machines by Using the Air-Gap Field Modulation Principle

by Wentao Zhang, Ying Fan, Z. Q. Zhu, Zhongze Wu, Wei Hua and Ming Cheng

World Electr. Veh. J. 2022, 13(11), 215; https://doi.org/10.3390/wevj13110215 - 17 Nov 2022

Viewed by 2098

Abstract

In order to analyze the DC winding induced voltage in the wound-rotor synchronous machine, this paper uses the air-gap field modulation principle to investigate its operation mechanism and harmonic order. By establishing the analytical magneto-motive force (MMF)-permeance model, the DC winding induced voltage [...] Read more.

In order to analyze the DC winding induced voltage in the wound-rotor synchronous machine, this paper uses the air-gap field modulation principle to investigate its operation mechanism and harmonic order. By establishing the analytical magneto-motive force (MMF)-permeance model, the DC winding induced voltage per electrical cycle under open-circuit condition, armature reaction condition and on-load condition are deduced. Analytical analysis shows that the MMF function, stator and rotor permeance function are critical factors that influence the harmonic order of the DC winding induced voltage. The analysis results are compared with those predicted by the finite element analysis (FEA). Both non-linear steel and linear steel conditions are accounted in the FEA analysis, and the results show that the analytical deduction result agrees well with the FEA analysis result. Full article

(This article belongs to the Special Issue Recent Advances in Novel Permanent Magnet and Magnetless Machines and Control for Electric Vehicles)

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16 pages, 3464 KiB

Open AccessArticle

Analysis of Charging Load Acceptance Capacity of Electric Vehicles in the Residential Distribution Network

by Yuan-Peng Hua, Shi-Qian Wang, Ding Han, Hong-Kun Bai, Yuan-Yuan Wang and Qiu-Yan Li

World Electr. Veh. J. 2022, 13(11), 214; https://doi.org/10.3390/wevj13110214 - 17 Nov 2022

Cited by 1 | Viewed by 1644

Abstract

After large-scale electric vehicles (EVs) are connected to the residential distribution network, community charging has become one of the main bottlenecks at present, especially in old residential areas. Therefore, the current residential distribution network’s ability to accept charging load and when and how [...] Read more.

After large-scale electric vehicles (EVs) are connected to the residential distribution network, community charging has become one of the main bottlenecks at present, especially in old residential areas. Therefore, the current residential distribution network’s ability to accept charging load and when and how the distribution network needs to be transformed have become meaningful research points. Based on the characteristics of the EVs’ charging load of residential areas on a typical day and the size of the target annual charging load, this paper analyzes the acceptance capacity of the charging load of the distribution network on typical weekdays and weekends. By taking the charging load characteristics, the charging time of EVs, the voltage of each node of the distribution network, the line capacity, the transformation capacity of the distribution station as constraints, and the maximum capacity of the residential distribution network to accept the charging load as the objective function, the charging load capacity of the residential distribution network is analyzed. The particle swarm optimization algorithm is employed to solve the optimized mathematical model. The simulation uses an actual residential distribution network as an analysis example, and the partition optimization results prove the correctness and feasibility of this proposed method. Full article

(This article belongs to the Special Issue Charging Infrastructure for EVs)

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15 pages, 1519 KiB

Open AccessEditor’s ChoiceArticle

Electrification of Vehicle Miles Traveled and Fuel Consumption within the Household Context: A Case Study from California, U.S.A.

by Ahmet Mandev, Frances Sprei and Gil Tal

World Electr. Veh. J. 2022, 13(11), 213; https://doi.org/10.3390/wevj13110213 - 15 Nov 2022

Cited by 4 | Viewed by 2646

Abstract

Plug-in electric vehicles (PEVs), consisting of battery electric vehicles (BEVs) and plug-in hybrid electric vehicles (PHEVs), combined with the decarbonization of the electricity sector, can significantly help reduce greenhouse gas emissions in the transport sector. This study used empirical data from 287 households [...] Read more.

Plug-in electric vehicles (PEVs), consisting of battery electric vehicles (BEVs) and plug-in hybrid electric vehicles (PHEVs), combined with the decarbonization of the electricity sector, can significantly help reduce greenhouse gas emissions in the transport sector. This study used empirical data from 287 households with at least one plug-in electric vehicle in California between 2016 and 2020. We estimated electric vehicle miles traveled (eVMT), fuel consumption and utility factor at the household level, i.e., taking into consideration all vehicles. We also studied the effect of household-specific factors—such as frequency of overlaps between vehicles, frequency of charging and frequency of long-distance trips—on eVMT, utility factor and fuel consumption within two-car households. Our results indicate that PHEVs with a range of at least 35 miles have the potential to electrify a similar share of total household miles as some short range BEVs, or can reach up to 70% as much electrification as some long range BEVs and, thus, can play an important role in decarbonizing the transport sector. Full article

(This article belongs to the Special Issue EVS35—International Electric Vehicle Symposium and Exhibition (Oslo, Norway))

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16 pages, 2233 KiB

Open AccessEditor’s ChoiceArticle

Regional Electric Vehicle Fast Charging Network Design Using Common Public Data

by Nathaniel S. Pearre, Lukas G. Swan, Erin Burbidge, Sarah Balloch, Logan Horrocks, Brendan Piper and Julia Anctil

World Electr. Veh. J. 2022, 13(11), 212; https://doi.org/10.3390/wevj13110212 - 10 Nov 2022

Cited by 3 | Viewed by 2631

Abstract

Electric vehicles rely on public fast charging when traveling outside a single charge range. Networks of fast charging hubs are a preferred solution, but should be deployed according to a design that avoids both redundant infrastructure representing overinvestment, and “charging deserts” which limit [...] Read more.

Electric vehicles rely on public fast charging when traveling outside a single charge range. Networks of fast charging hubs are a preferred solution, but should be deployed according to a design that avoids both redundant infrastructure representing overinvestment, and “charging deserts” which limit travel by EVs and thus inhibit EV adoption. We present a two-stage design strategy for a network of charging hubs relying on common public data including maps of roadways and electrical systems, and ubiquitous and readily accessible daily traffic volume data. First, the network design is based on the electrical distribution system, roadways, and a target inter-hub driving distance. Second, the number of fast chargers necessary at each hub to support expected vehicle kilometers is determined such that queuing to charge is infrequent. A case study to prepare Nova Scotia, Canada for the 2030 electric fleet of 15% of vehicles results in a network design with an average hub catchment area of 1230 km² and 354 electric vehicles per fast charger, and ensures that they are equitably distributed and can enable travel by EV throughout the jurisdiction. Full article

(This article belongs to the Special Issue Charging Infrastructure for EVs)

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12 pages, 4965 KiB

Open AccessArticle

Research on Radiated Immunity Test Methods for ADAS Functions Considering Vehicle In-the-Loop

by Yanming Qin, Aihua Tang, Jin Jia, Lei Wan, Heming Zhao and Yun Long

World Electr. Veh. J. 2022, 13(11), 211; https://doi.org/10.3390/wevj13110211 - 9 Nov 2022

Cited by 3 | Viewed by 2369

Abstract

The radiated immunity of passenger cars and commercial vehicles is validated using electromagnetic interference from off-vehicle radiation sources in an anechoic chamber according to the procedure in ISO 11451-2. Common electrical or electronic vehicle systems, including dual flash, monitors, and entertainment systems, must [...] Read more.

The radiated immunity of passenger cars and commercial vehicles is validated using electromagnetic interference from off-vehicle radiation sources in an anechoic chamber according to the procedure in ISO 11451-2. Common electrical or electronic vehicle systems, including dual flash, monitors, and entertainment systems, must be validated using a standardized immunity evaluation procedure. However, Automated Driver Assistance System (ADAS) functions often lack verification in complex electromagnetic fields, which might create potential risk due to electromagnetic compatibility problems. For example, radar and camera sensors based on autonomous emergency braking (AEB), adaptive cruise control (ACC), or lane departure warning (LDW) functions may be ineffective in the real world if subjected to electromagnetic interference. This paper presents a new methodology to evaluate vehicle immunity performance based on the main ADAS functions. A target simulator and a virtual driving environment are designed to trigger AEB, ACC, and LDW functions in an anechoic chamber. Moreover, the vehicle In-the-Loop (VHIL) conception is also applied by acquiring and analyzing key ADAS-related signals. The reliability of ADAS functions at the whole-vehicle level can be evaluated and improved using standardized external radiation sources. Full article

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20 pages, 3115 KiB

Open AccessArticle

Analysis and Roll Prevention Control for Distributed Drive Electric Vehicles

by Xiaoyu Chang, Huanhuan Zhang, Shuai Yan, Shengli Hu and Youming Meng

World Electr. Veh. J. 2022, 13(11), 210; https://doi.org/10.3390/wevj13110210 - 7 Nov 2022

Cited by 3 | Viewed by 2117

Abstract

This work presents an approach to improve the roll stability of distributed drive electric vehicles (DDEV). The effect of the reaction torque from the in-wheel motor exerts additional roll moment, which is different from traditional vehicles. The additional roll moment can be achieved [...] Read more.

This work presents an approach to improve the roll stability of distributed drive electric vehicles (DDEV). The effect of the reaction torque from the in-wheel motor exerts additional roll moment, which is different from traditional vehicles. The additional roll moment can be achieved by active control of the wheel torque adjustment, which achieves a control effect similar to the active suspension. The anti-roll control strategy of decoupling control of roll motion and yaw motion are proposed. The direct yaw moment is calculated by the linear quadratic regulator (LQR) algorithm while the additional rolling moment is calculated by the sliding mode variable structure. For maneuvering rollover caused by excessive lateral acceleration, an anti-rollover control strategy is designed based on differential braking. A fuzzy control theory is used to decide the yaw moment to be compensated. The distribution method of the braking torque applied to the outer wheel alone, and the lateral load transfer rate is the main evaluation index for simulation verification of typical working conditions. The simulation results show that the proposed control strategy for DDEV is effective. Full article

(This article belongs to the Special Issue Advanced X-by-Wire Technologies in Design, Control and Measurement for Vehicular Electrified Chassis)

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18 pages, 6619 KiB

Open AccessArticle

Drivability Optimization of Electric Vehicle Drivetrains for Brake Blending Maneuvers

by Andreas Koch, Jonas Brauer and Jens Falkenstein

World Electr. Veh. J. 2022, 13(11), 209; https://doi.org/10.3390/wevj13110209 - 4 Nov 2022

Cited by 2 | Viewed by 2063

Abstract

Electric vehicle drivetrains are considered a way to reduce greenhouse gas emissions from road traffic. The use of electric drives in automotive vehicles offers advantages, such as the potential to recover energy during braking (regenerative braking). The limitation of the maximum air gap [...] Read more.

Electric vehicle drivetrains are considered a way to reduce greenhouse gas emissions from road traffic. The use of electric drives in automotive vehicles offers advantages, such as the potential to recover energy during braking (regenerative braking). The limitation of the maximum air gap torque of the vehicle drive machine by several factors requires a temporary standalone or simultaneous use of the conventional vehicle wheel brake. In several studies, it is shown that during braking operations, the drive machine and the vehicle wheel brake can induce torsional oscillations in the drivetrain, which have a negative influence on the driving comfort and lead to a high mechanical load. To reduce these oscillations, the simultaneous use of an active anti-jerk control is necessary. Due to the problem of oscillation excitations caused by a brake intervention, the used drivability function (integrated prefilter, anti-jerk control) is investigated and optimized with regard to brake blending maneuvers and the effectiveness for damping torsional oscillations. Therefore, the dynamics of the drivetrain are adapted to the dynamics of the braking system using the prefilter, which leads to precise fulfilment of the driver’s braking desire, even during dynamic brake blending maneuvers. All investigations are carried out with a hardware-in-the-loop test bench to create reproducible results. Full article

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14 pages, 4014 KiB

Open AccessArticle

Intelligent Motor Bearing Fault Diagnosis Using Channel Attention-Based CNN

by Jianguo Yin and Gang Cen

World Electr. Veh. J. 2022, 13(11), 208; https://doi.org/10.3390/wevj13110208 - 3 Nov 2022

Cited by 8 | Viewed by 2175

Abstract

Many components of electric vehicles contain rolling bearings, and the operating condition of rolling bearings often affects the operating performance of electric vehicles. Monitoring the operating status of the bearings is one of the key technologies to ensure the safe operation of the [...] Read more.

Many components of electric vehicles contain rolling bearings, and the operating condition of rolling bearings often affects the operating performance of electric vehicles. Monitoring the operating status of the bearings is one of the key technologies to ensure the safe operation of the bearings. We propose a channel attention-based convolutional neural network (CA-CNN) model for rolling bearing fault diagnosis. The model can directly use the raw vibration signal of the bearing as input to achieve bearing fault diagnosis under different operating loads and different noise environments. The experimental results show that, compared with other intelligent diagnosis methods, the proposed model CA-CNN achieves a high diagnostic accuracy under different load cases and still has advantages in different noisy environments. It is also beneficial to promote the intelligent fault diagnosis and maintenance of electric vehicles. Full article

(This article belongs to the Special Issue Electrical Machines Design and Control in Electric Vehicles)

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18 pages, 3748 KiB

Open AccessReview

Driver Identification Methods in Electric Vehicles, a Review

by Dengfeng Zhao, Junjian Hou, Yudong Zhong, Wenbin He, Zhijun Fu and Fang Zhou

World Electr. Veh. J. 2022, 13(11), 207; https://doi.org/10.3390/wevj13110207 - 3 Nov 2022

Cited by 3 | Viewed by 2213

Abstract

Driver identification is very important to realizing customized service for drivers and road traffic safety for electric vehicles and has become a research hotspot in the field of modern automobile development and intelligent transportation. This paper presents a comprehensive review of driver identification [...] Read more.

Driver identification is very important to realizing customized service for drivers and road traffic safety for electric vehicles and has become a research hotspot in the field of modern automobile development and intelligent transportation. This paper presents a comprehensive review of driver identification methods. The basic process of driver identification task is proposed as four steps, the advantages and disadvantages of different data sources for driver identification are analyzed, driver identification models are divided into three categories, and the characteristics and research progress of driver identification models are summarized, which can provide a reference for further research on driver identification. It is concluded that on-board sensor data in the natural driving state is objective and accurate and could be the main data source for driver identification. Emerging technologies such as big data, artificial intelligence, and the internet of things have contributed to building a deep learning hybrid model with high accuracy and robustness and representing an important gradual development trend of driver identification methods. Developing a driver identification method with high accuracy, real-time performance, and robustness is an important development goal in the future. Full article

(This article belongs to the Topic Advanced Electric Vehicle Technology)

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15 pages, 3339 KiB

Open AccessArticle

Analysis, Design, and Experimental Results for a High-Frequency ZVZCS Galvanically Isolated PSFB DC-DC Converter over a Wide Operating Range Using GaN-HEMT

by Abdullah Eial Awwad

World Electr. Veh. J. 2022, 13(11), 206; https://doi.org/10.3390/wevj13110206 - 2 Nov 2022

Cited by 2 | Viewed by 2126

Abstract

This paper investigates the potential of the emerging gallium nitride (GaN) high-electron mobility transistors (HEMT) power devices to meet certain power conversion challenges. The advantages of utilizing GaN HEMT transistors in a high-frequency, high-power isolated DC-DC topology are explored experimentally. Using the GaN [...] Read more.

This paper investigates the potential of the emerging gallium nitride (GaN) high-electron mobility transistors (HEMT) power devices to meet certain power conversion challenges. The advantages of utilizing GaN HEMT transistors in a high-frequency, high-power isolated DC-DC topology are explored experimentally. Using the GaN HEMT’s parasitic elements, e.g., output capacitance, and the leakage inductance of the transformer, a soft switching zero-voltage zero-current switching (ZVZCS) phase shift converter is proposed. Accordingly, the freewheeling current is terminated, and soft switching is realized for most of the primary and secondary active devices. Furthermore, without using any additional circuitry, the overshoot voltage across the bridges of active rectifier diodes is clamped at their voltage level. In addition, a high-frequency power transformer is optimized to minimize the overall transformer losses (e.g., winding and core losses). Combined the conductor types, e.g., litz wire and copper foil, shows good electrical and thermal performance by reducing the AC and DC resistance. Finally, a 5 kW, 100–250 kHz prototype is built and tested. The experimental results show a conversion efficiency of up to 98.18% for the whole converter. Full article

(This article belongs to the Topic Power Converters)

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17 pages, 3418 KiB

Open AccessArticle

Trajectory Tracking Control of Intelligent X-by-Wire Vehicles

by Zixu Wang, Yong Li, Chuyo Kaku and Hongyu Zheng

World Electr. Veh. J. 2022, 13(11), 205; https://doi.org/10.3390/wevj13110205 - 1 Nov 2022

Cited by 3 | Viewed by 1856

Abstract

Vehicle intelligence is an effective way to improve driving safety and comfort and reduce traffic accidents. The trajectory tracking control of unmanned vehicles is the core module of intelligent vehicles. As a redundant system, the X-by-wire electric vehicle has the advantage that the [...] Read more.

Vehicle intelligence is an effective way to improve driving safety and comfort and reduce traffic accidents. The trajectory tracking control of unmanned vehicles is the core module of intelligent vehicles. As a redundant system, the X-by-wire electric vehicle has the advantage that the turning angles and driving torque of the four wheels can be precisely controlled and it has a higher degree of controllability and flexibility. In this paper, a trajectory tracking control algorithm based on a hierarchical control architecture is designed based on x-by-wire vehicles. The hierarchical control algorithm architecture includes the trajectory tracking layer, tire force distribution layer, and actuator control layer. The trajectory tracking layer uses the longitudinal force, lateral force, and yaw moment as the control variables; the model predictive control algorithm controls the vehicle to follow the desired trajectory. The tire force distribution layer is solved by transforming the tire force distribution problem into a quadratic programming problem with constraints. Based on the expected resultant force and resultant moment, the longitudinal force and lateral force of each tire in the vehicle coordinate system are obtained. The actuator control layer converts the coordinate system to obtain the longitudinal force and lateral force in the tire coordinate system, which uses the arctangent function tire model to solve the desired tire slip angle, and then obtains the vehicle steer angle and driving torque. To verify the effectiveness of the trajectory tracking control algorithm of the hierarchical control architecture, the proposed trajectory tracking control algorithm is simulated and verified through the variable speed double line change condition and the low road friction coefficient double line change condition. The simulation results show that the control algorithm proposed in this paper has the accuracy to follow the desired trajectory.Definition: Full article

(This article belongs to the Special Issue Advanced X-by-Wire Technologies in Design, Control and Measurement for Vehicular Electrified Chassis)

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41 pages, 3425 KiB

Open AccessFeature PaperReview

Electric Vehicle Air Conditioning System and Its Optimization for Extended Range—A Review

by Sherin Sam Jose and Ramesh Kumar Chidambaram

World Electr. Veh. J. 2022, 13(11), 204; https://doi.org/10.3390/wevj13110204 - 1 Nov 2022

Cited by 9 | Viewed by 7714

Abstract

Environmental protection initiatives are speeding up the replacement of the present IC engine-based transportation system with an electric motor-driven system. In electric vehicles (EV), energy stored in batteries is used for the traction of the vehicle and the operation of the auxiliaries. The [...] Read more.

Environmental protection initiatives are speeding up the replacement of the present IC engine-based transportation system with an electric motor-driven system. In electric vehicles (EV), energy stored in batteries is used for the traction of the vehicle and the operation of the auxiliaries. The range of the electric vehicle was identified to be one of the major challenges faced by the EV segment. The optimization of the consumption of stored energy is the best solution for range improvement in an EV. Auxiliaries in the vehicle include basic accessories such as a lighting system and equipment for improved comfort such as air conditioners. Air conditioning equipment is the major power-consuming auxiliary in an EV apart from the traction motor. This review article discusses the significance and influence of different components of the air conditioning system, and methods followed by researchers to optimize the performance and reduce the energy consumption of the air conditioning system to extend the range of vehicles. The effects of thermal load and volume of space to be conditioned were also considered in this study. This review concludes by stating the different possibilities for the reduction in power consumption and emphasizes zonal air conditioning of occupant space as a solution for reducing energy consumption or increasing the range of EVs. Compared to full-space air conditioning, zonal AC can reduce power consumption by up to 51%. Full article

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18 pages, 5992 KiB

Open AccessArticle

Vehicle Safety Planning Control Method Based on Variable Gauss Safety Field

by Zixuan Zhu, Chenglong Teng, Yingfeng Cai, Long Chen, Yubo Lian and Hai Wang

World Electr. Veh. J. 2022, 13(11), 203; https://doi.org/10.3390/wevj13110203 - 31 Oct 2022

Cited by 3 | Viewed by 1472

Abstract

The existing intelligent vehicle trajectory-planning methods have limitations in terms of efficiency and safety. To overcome these limitations, this paper proposes an automatic driving trajectory-planning method based on a variable Gaussian safety field. Firstly, the time series bird’s-eye view is used as the [...] Read more.

The existing intelligent vehicle trajectory-planning methods have limitations in terms of efficiency and safety. To overcome these limitations, this paper proposes an automatic driving trajectory-planning method based on a variable Gaussian safety field. Firstly, the time series bird’s-eye view is used as the input state quantity of the network, which improves the effectiveness of the trajectory planning policy network in extracting the features of the surrounding traffic environment. Then, the policy gradient algorithm is used to generate the planned trajectory of the autonomous vehicle, which improves the planning efficiency. The variable Gaussian safety field is used as the reward function of the trajectory planning part and the evaluation index of the control part, which improves the safety of the reinforcement learning vehicle tracking algorithm. The proposed algorithm is verified using the simulator. The obtained results show that the proposed algorithm has excellent trajectory planning ability in the highway scene and can achieve high safety and high precision tracking control. Full article

(This article belongs to the Special Issue Advanced X-by-Wire Technologies in Design, Control and Measurement for Vehicular Electrified Chassis)

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12 pages, 3111 KiB

Open AccessArticle

Research into the Regenerative Braking of an Electric Car in Urban Driving

by Dainis Berjoza, Vilnis Pirs and Inara Jurgena

World Electr. Veh. J. 2022, 13(11), 202; https://doi.org/10.3390/wevj13110202 - 27 Oct 2022

Cited by 6 | Viewed by 5953

Abstract

As the use of fossil energy sources in transport declines, new technologies, e.g., electric vehicles, are being introduced. One of the advantages of electric vehicles in urban driving is the possibility to charge their batteries with regenerative energy during braking. For this reason, [...] Read more.

As the use of fossil energy sources in transport declines, new technologies, e.g., electric vehicles, are being introduced. One of the advantages of electric vehicles in urban driving is the possibility to charge their batteries with regenerative energy during braking. For this reason, electric cars usually have a longer range per charge in urban driving than in non-urban driving. This research experimentally examined the regenerative braking of a converted Renault Clio electric car at different regenerative braking settings in the range of 0–100%. An original research methodology was developed for road tests in urban driving. The driving cycle included aggressive driving with rapid acceleration and braking. The road test was conducted in second and third gears, which are the usual gears for driving an electric car in a city. The highest regenerative braking efficiencies were achieved at a 100% setting, which in some replications reached 24% of the total electrical energy consumed; however, the 100% setting was too high from the perspective of comfortable driving of the electric car and contributed to a too significant increase in the braking force at the initial stages of braking. Full article

(This article belongs to the Topic Energy Management and Efficiency in Electric Motors, Drives, Power Converters and Related Systems)

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20 pages, 6144 KiB

Open AccessArticle

LiDAR-Only Ground Vehicle Navigation System in Park Environment

by Kezhi Wang, Jianyu Li, Meng Xu, Zonghai Chen and Jikai Wang

World Electr. Veh. J. 2022, 13(11), 201; https://doi.org/10.3390/wevj13110201 - 27 Oct 2022

Cited by 2 | Viewed by 2079

Abstract

In this paper, a novel and complete navigation system is proposed for mobile ground vehicles in a park environment. LiDAR map representation and maintenance, dynamic objects detection and removal, hierarchal path planning and model-free local planning are developed in the system. The system [...] Read more.

In this paper, a novel and complete navigation system is proposed for mobile ground vehicles in a park environment. LiDAR map representation and maintenance, dynamic objects detection and removal, hierarchal path planning and model-free local planning are developed in the system. The system is formulated in three layers. In the global layer, given the global point cloud map of the environment, the traverse area is detected and its skeleton graph is extracted to represent the global topology of the environment. Then, in the middle layer, the global map is divided into several submaps and each submap is represented by a modified multi-layer grid map. In the local layer, considering the dynamics of the environment, according to the real-time LiDAR observation, a probabilistic distribution-based representation and its updating mechanism are proposed. Based on the hierarchal environment map representation, the path planning and local planning are performed in a hierarchal way. Considering the complexity of the motion model estimation, a model free local planner is used. Extensive experiments are conducted in the real environment and the source code will be made open for the robotics community. Full article

(This article belongs to the Special Issue Theory, Method and Application of New Energy and Intelligent Transportation)

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19 pages, 6160 KiB

Open AccessArticle

Nonlinear MPC-Based Acceleration Slip Regulation for Distributed Electric Vehicles

by Wentong Shi, Yuyao Jiang, Zuying Shen, Zhongjing Yu, Hongqing Chu and Dengcheng Liu

World Electr. Veh. J. 2022, 13(11), 200; https://doi.org/10.3390/wevj13110200 - 27 Oct 2022

Cited by 3 | Viewed by 1945

Abstract

To address the problem in which wheel longitudinal slip rate directly affects the dynamics and handling stability of a vehicle under driving conditions, front and rear dual-motor four-wheel drive electric vehicles (4WD EVs) were selected as the research object in this study. An [...] Read more.

To address the problem in which wheel longitudinal slip rate directly affects the dynamics and handling stability of a vehicle under driving conditions, front and rear dual-motor four-wheel drive electric vehicles (4WD EVs) were selected as the research object in this study. An acceleration slip regulation (ASR) control strategy based on nonlinear model predictive control (NMPC) is proposed. First, the vehicle dynamics model and the Simulink/CarSim co-simulation platform were built. Second, an ASR controller with intervention and exit mechanisms was designed with the control objective of tracking reference speed or optimal slip rate. Then, considering the problem that the left and right wheels could not freely distribute torque under the condition of a split road surface, the motor output torque was determined in accordance with the wheel with the larger slip rate to enhance passibility. Finally, on the basis of the built Simulink/CarSim co-simulation platform, slip rate control simulation experiments were performed on a snow-covered road, a wet asphalt road, a docking road, and a split road. The designed controller can better track target slip rate and it exhibits better dynamic performance and stability than the method with PID control under different road conditions, especially under low speed and low adhesion road conditions, and its robustness can also meet the requirements. Full article

(This article belongs to the Special Issue Advanced X-by-Wire Technologies in Design, Control and Measurement for Vehicular Electrified Chassis)

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16 pages, 5529 KiB

Open AccessArticle

Comparative Analysis and Design of Double-Rotor Stator-Permanent-Magnet Motors with Magnetic-Differential Application for Electric Vehicles

by Tengbo Yang, Kwok Tong Chau, Wei Liu, Tze Wood Ching and Libing Cao

World Electr. Veh. J. 2022, 13(11), 199; https://doi.org/10.3390/wevj13110199 - 26 Oct 2022

Cited by 3 | Viewed by 3301

Abstract

In order to get rid of the bulky and lossy differential gears and to enhance the system robustness, the magnetic differential (MagD) system is proposed after the mechanical differential (MechD) and electronic differential (ElecD) systems. The MagD system is mainly composed of the [...] Read more.

In order to get rid of the bulky and lossy differential gears and to enhance the system robustness, the magnetic differential (MagD) system is proposed after the mechanical differential (MechD) and electronic differential (ElecD) systems. The MagD system is mainly composed of the double-rotor (DR) stator-permanent-magnet (PM) motor with a new set of winding whose magnetic field reversely interacts with the PM field in two rotors. As a result, the compactness and reliability of the system are improved. This paper quantitatively compares and analyzes the three major types of stator-PM motors applied in the MagD system, which can give an essential guideline on the choice of motor types in various situations. All kinds of motors are optimized in the same exercise, and their performances are thoroughly evaluated and compared by using three-dimensional finite element analysis. Finally, the motor with the best overall performance is prototyped, and the MagD system is set up for experimental verification of the optimized flux-switching PM motor. Full article

(This article belongs to the Special Issue Recent Advances in Novel Permanent Magnet and Magnetless Machines and Control for Electric Vehicles)

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19 pages, 4401 KiB

Open AccessArticle

Non-Intrusive Load Monitoring and Controllability Evaluation of Electric Vehicle Charging Stations Based on K-Means Clustering Optimization Deep Learning

by Shixiang Lu, Xiaofeng Feng, Guoying Lin, Jiarui Wang and Qingshan Xu

World Electr. Veh. J. 2022, 13(11), 198; https://doi.org/10.3390/wevj13110198 - 25 Oct 2022

Cited by 2 | Viewed by 1739

Abstract

Electric vehicles have the advantages of zero emissions and high energy efficiency. They have a broad potential in today’s social life, especially in China where they have been widely used. In the current situation, whereby the storage capacity of electric vehicles is continually [...] Read more.

Electric vehicles have the advantages of zero emissions and high energy efficiency. They have a broad potential in today’s social life, especially in China where they have been widely used. In the current situation, whereby the storage capacity of electric vehicles is continually increasing and the requirements for grid stability are getting higher and higher, V2G technology emerges to keep up with the times. Since the electric vehicle charging station is a large-scale electric vehicle cluster charging terminal, it is necessary to pay attention to the status and controllability of each charging pile. In view of the lack of attention to the actual operation of the electric vehicle charging station in the existing vehicle–network interaction mode, the charging state of the current electric vehicle charging station is fixed. In this paper, deep learning is used to establish a load perception model for electric vehicle charging stations, and K-means clustering is used to optimize the load perception model to realize random load perception and non-intrusive load monitoring stations for electric vehicle charging. The calculation example results show that the proposed method has good performance in the load perception and controllability evaluation of electric vehicle charging stations, and it provides a feasible solution for the practical realization of electric vehicle auxiliary response. Full article

(This article belongs to the Special Issue Novel Electric Vehicle Technology towards Low Carbon Future: Advanced Powertrain, Energy Management and Grid Interaction)

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20 pages, 3744 KiB

Open AccessEditor’s ChoiceArticle

Benefits of an Electric Road System for Battery Electric Vehicles

by Wasim Shoman, Sten Karlsson and Sonia Yeh

World Electr. Veh. J. 2022, 13(11), 197; https://doi.org/10.3390/wevj13110197 - 24 Oct 2022

Cited by 13 | Viewed by 6171

Abstract

Electric road systems (ERS)—infrastructure that allows for charging while driving—are currently considered in Sweden for electrifying long-haul trucking. The technology can also charge battery electric passenger vehicles (BEVs). This study utilizes real-world car movement data in Sweden and detailed spatial analysis to explore [...] Read more.

Electric road systems (ERS)—infrastructure that allows for charging while driving—are currently considered in Sweden for electrifying long-haul trucking. The technology can also charge battery electric passenger vehicles (BEVs). This study utilizes real-world car movement data in Sweden and detailed spatial analysis to explore to what extent ERS could displace stationary charging if it is available for BEVs and the expected benefits. We find that ERS utilization and the minimum battery ranges depend more on visited locations and home locations and less on the annual travel distances of car users. The median battery ranges required by rural residents are 15–18% greater than for urban residents. Our scenarios suggest that a mix of ERS and home-charging would achieve the most significant benefits. ERS with home charging reduces the required battery range by 62–71% in the main scenarios, and the net savings from smaller BEV batteries exceed the cost of ERS. Eliminating all stationary charging is feasible for many but not all vehicles. Utilizing ERS could also significantly reduce peak BEV charging by distributing charging throughout the day. We also find that there is a considerable difference between the maximum possible and minimum needed charging on ERS, which can significantly influence ERS revenues. Future studies can expand to include other modes (e.g., trucks) to provide more holistic assessments of economic benefits and charging needs. Full article

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16 pages, 4000 KiB

Open AccessArticle

Bidirectional Converter for Plug-In Hybrid Electric Vehicle On-Board Battery Chargers with Hybrid Technique

by Gopinath Anjinappa, Divakar Bangalore Prabhakar and Wen-Cheng Lai

World Electr. Veh. J. 2022, 13(11), 196; https://doi.org/10.3390/wevj13110196 - 22 Oct 2022

Cited by 7 | Viewed by 2468

Abstract

Recently, Plug-in Hybrid Electric Vehicles (PHEVs) have gathered a lot of attention by integrating an electric motor with an Internal Combustion Engine (ICE) to minimize fuel consumption and greenhouse gas emissions. The On-Board Chargers (OBCs) are selected in this research because they are [...] Read more.

Recently, Plug-in Hybrid Electric Vehicles (PHEVs) have gathered a lot of attention by integrating an electric motor with an Internal Combustion Engine (ICE) to minimize fuel consumption and greenhouse gas emissions. The On-Board Chargers (OBCs) are selected in this research because they are limited by dimensions and mass, and also consume low amounts of power. The Equivalent Series Resistance (ESR) of a filter capacitor is minor, so the zero produced by the ESR is positioned at a high frequency. In this state, the system magnitude gradually drops, causing a ripple in the circuit that generates a harmful impact on the battery’s stability. To improve the stability of the system, a Neural Network with an Improved Particle Swarm Optimization (NN–IPSO) control algorithm was developed. This study establishes an isolated converter topology for PHEVs to preserve battery-charging functions through a lesser number of power electronic devices over the existing topology. This isolated converter topology is controlled by NN–IPSO for the PHEV, which interfaces with the battery. The simulation results were validated in MATLAB, indicating that the proposed NN–IPSO-based isolated converter topology minimizes the Total Harmonic Distortion (THD) to 3.69% and the power losses to 0.047 KW, and increases the efficiency to 99.823%, which is much better than that of the existing Switched Reluctance Motor (SRM) power train topology. Full article

(This article belongs to the Special Issue Artificial Intelligence Applied to Edge Computing of Electric Vehicle Applications)

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World Electr. Veh. J., Volume 13, Issue 11 (November 2022) – 25 articles

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