World Electric Vehicle Journal

25 pages, 7898 KiB

Open AccessArticle

Rolling Bearing Fault Diagnosis Based on Optimized VMD Combining Signal Features and Improved CNN

by Yingyong Zou, Xingkui Zhang, Wenzhuo Zhao and Tao Liu

World Electr. Veh. J. 2024, 15(12), 544; https://doi.org/10.3390/wevj15120544 - 22 Nov 2024

Aiming at the problem that the vibration signals of rolling bearings in high-speed rail traction motors are often affected by noise when they are in a fault state, which makes it very difficult to extract the fault features during fault diagnosis and causes [...] Read more.

Aiming at the problem that the vibration signals of rolling bearings in high-speed rail traction motors are often affected by noise when they are in a fault state, which makes it very difficult to extract the fault features during fault diagnosis and causes obstruction in fault classification. The article proposes a rolling bearing fault diagnosis based on optimized variational mode decomposition (VMD) combined with signal features and an improved convolutional neural network (CNN). The golden jackal optimization (GJO) algorithm is employed to optimize the key parameters of the VMD, enabling effective signal decomposition. The decomposed signals are then filtered and reconstructed using criteria based on kurtosis and interrelationship measures. The time-domain features of the reconstructed signals are computed, and the feature vectors are constructed, which are used as inputs to the deep learning network; the CNN combined with the support vector machine (SVM) network model is used for the extraction of the features and the classification of the faults. The experimental results show that the method can effectively extract fault features in noise-covered signals, and the accuracy is also significantly improved compared with traditional methods. Full article

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20 pages, 11953 KiB

Open AccessArticle

Direct Power Control of Vienna Rectifier Based on Fractional Order Sliding Mode Control

by Tao Wang, Shenhui Chen, Xin Li, Jihui Zhang and Jinghao Ma

World Electr. Veh. J. 2024, 15(12), 543; https://doi.org/10.3390/wevj15120543 - 22 Nov 2024

Abstract

Taking a Vienna rectifier as the research object, the power mathematical model based on a switching function is established according to its working principle. A sliding mode variable structure control algorithm based on the reaching law is examined in order to address the [...] Read more.

Taking a Vienna rectifier as the research object, the power mathematical model based on a switching function is established according to its working principle. A sliding mode variable structure control algorithm based on the reaching law is examined in order to address the issues of the slow response speed and inadequate anti-interference of classical PI control in the face of abrupt changes in the DC-side load. In response to the sluggish convergence rate and inadequate chattering suppression of classical integer order sliding mode control, a fractional order exponential reaching law sliding mode, direct power control approach with rapid convergence is developed. The fractional calculus is introduced into the sliding mode control, and the dynamic performance and convergence speed of the control system are improved by increasing the degree of freedom of the fractional calculus operator. The method of including a balance factor in the zero-sequence component is employed to address the issue of the midpoint potential equilibrium in the Vienna rectifier. Ultimately, the suggested control is evaluated against classical PI control through simulation analysis and experimental validation. The findings indicate that the proposed technique exhibits rapid convergence, reduced control duration, and enhanced robustness, hence augmenting its resistance to interference. Full article

(This article belongs to the Special Issue Intelligent Electric Vehicle Control, Testing and Evaluation)

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16 pages, 6355 KiB

Open AccessArticle

The Impact of Wafters on the Thermal Properties and Performance of In-Wheel Motor

by Muhammad Hasan Albana, Ary Bachtiar Khrisna Putra and Harus Laksana Guntur

World Electr. Veh. J. 2024, 15(12), 542; https://doi.org/10.3390/wevj15120542 - 21 Nov 2024

Abstract

Electric vehicle (EV) proliferation is accelerating, characterized by the rising quantity of electric automobiles on global roadways. The electric machine is a crucial component of an EV, and the heat generated within the motor requires consideration as it impacts performance and longevity. A [...] Read more.

Electric vehicle (EV) proliferation is accelerating, characterized by the rising quantity of electric automobiles on global roadways. The electric machine is a crucial component of an EV, and the heat generated within the motor requires consideration as it impacts performance and longevity. A prevalent form of machine in EV is the in-wheel motor (IWM), which is notable for its compact size. However, it presents more significant cooling challenges. This research offers a new cooling method to cool the IWM. The system consists of wafters mounted on the housing of the IWM. Testing was conducted to determine the effect of wafters on the thermal properties and performance of IWMs. The machine used in this research is a brushless direct current (BLDC) motor featuring an outer rotor configuration and a peak power output of 1.5 kW. Testing was carried out experimentally and by simulation, and the simulation used Ansys Motor-CAD software. The research results show that applying wafers to IWM reduces the temperature of IWM components by up to 13.1%. IWM with wafters results in a torque increase of 0.14%, a power increase of 0.64%, and an efficiency improvement of 0.6% compared to IWM without wafters. Full article

(This article belongs to the Special Issue Design, Analysis and Optimization of Electrical Machines and Drives for Electric Vehicles, 2nd Edition)

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17 pages, 1206 KiB

Open AccessArticle

Multi-Criteria Analysis of Electric Vehicle Motor Technologies: A Review

by Emmanuel Kinoti, Mosetlhe Thapelo and Yusuff Adedayo

World Electr. Veh. J. 2024, 15(12), 541; https://doi.org/10.3390/wevj15120541 - 21 Nov 2024

Abstract

The electric vehicle market is constantly evolving, with the research and development efforts to improve motor technologies and address the current challenges to meet the growing demand for sustainable transportation solutions well underway. Electric vehicles are crucial to the global initiative to reduce [...] Read more.

The electric vehicle market is constantly evolving, with the research and development efforts to improve motor technologies and address the current challenges to meet the growing demand for sustainable transportation solutions well underway. Electric vehicles are crucial to the global initiative to reduce carbon emissions. The core component of an electric vehicle is its motor drive technology, which has undergone significant advancements and diversification in recent years. Although alternating-current motors, particularly induction and synchronous motors, are widely used for their efficiency and low maintenance, direct-current motors provide high torque and cost-effectiveness advantages. This study examines various electric motor technologies used in electric vehicles and compares them using several parameters, such as reliability, cost, and efficiency. This study presents a multi-criteria comparison of the various electric motors used in the electric traction system to provide a picture that enables selecting the appropriate electrical motor for the intended application. Although the permanent magnet synchronous motor appears to be the popular choice among electric car makers, the proposed comparative study demonstrates that the induction motor matches the essential requirements of electric vehicles. Full article

(This article belongs to the Special Issue Dynamic Modeling, Identification, and Advanced Control of Intelligent Electric Vehicles)

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18 pages, 1518 KiB

Open AccessArticle

VAS-3D: A Visual-Based Alerting System for Detecting Drowsy Drivers in Intelligent Transportation Systems

by Hadi El Zein, Hassan Harb, François Delmotte, Oussama Zahwe and Samir Haddad

World Electr. Veh. J. 2024, 15(12), 540; https://doi.org/10.3390/wevj15120540 - 21 Nov 2024

Abstract

Nowadays, driving accidents are considered one of the most crucial challenges for governments and communities that affect transportation systems and peoples lives. Unfortunately, there are many causes behind the accidents; however, drowsiness is one of the main factors that leads to a significant [...] Read more.

Nowadays, driving accidents are considered one of the most crucial challenges for governments and communities that affect transportation systems and peoples lives. Unfortunately, there are many causes behind the accidents; however, drowsiness is one of the main factors that leads to a significant number of injuries and deaths. In order to reduce its effect, researchers and communities have proposed many techniques for detecting drowsiness situations and alerting the driver before an accident occurs. Mostly, the proposed solutions are visually-based, where a camera is positioned in front of the driver to detect their facial behavior and then determine their situation, e.g., drowsy or awake. However, most of the proposed solutions make a trade-off between detection accuracy and speed. In this paper, we propose a novel Visual-based Alerting System for Detecting Drowsy Drivers (VAS-3D) that ensures an optimal trade-off between the accuracy and speed metrics. Mainly, VAS-3D consists of two stages: detection and classification. In the detection stage, we use pre-trained Haar cascade models to detect the face and eyes of the driver. Once the driver’s eyes are detected, the classification stage uses several pre-trained Convolutional Neural Network (CNN) models to classify the driver’s eyes as either open or closed, and consequently their corresponding situation, either awake or drowsy. Subsequently, we tested and compared the performance of several CNN models, such as InceptionV3, MobileNetV2, NASNetMobile, and ResNet50V2. We demonstrated the performance of VAS-3D through simulations on real drowsiness datasets and experiments on real world scenarios based on real video streaming. The obtained results show that VAS-3D can enhance the accuracy detection of drowsy drivers by at least

7.5 %

(the best accuracy reached was

95.5 %

) and the detection speed by up to

57 %

(average of

0.25

ms per frame) compared to other existing models. Full article

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

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17 pages, 8599 KiB

Open AccessArticle

Att-BEVFusion: An Object Detection Algorithm for Camera and LiDAR Fusion Under BEV Features

by Peicheng Shi, Mengru Zhou, Xinlong Dong and Aixi Yang

World Electr. Veh. J. 2024, 15(11), 539; https://doi.org/10.3390/wevj15110539 - 20 Nov 2024

Abstract

To improve the accuracy of detecting small and long-distance objects while self-driving cars are in motion, in this paper, we propose a 3D object detection method, Att-BEVFusion, which fuses camera and LiDAR data in a bird’s-eye view (BEV). First, the transformation from the [...] Read more.

To improve the accuracy of detecting small and long-distance objects while self-driving cars are in motion, in this paper, we propose a 3D object detection method, Att-BEVFusion, which fuses camera and LiDAR data in a bird’s-eye view (BEV). First, the transformation from the camera view to the BEV space is achieved through an implicit supervision-based method, and then the LiDAR BEV feature point cloud is voxelized and converted into BEV features. Then, a channel attention mechanism is introduced to design a BEV feature fusion network to realize the fusion of camera BEV feature space and LiDAR BEV feature space. Finally, regarding the issue of insufficient global reasoning in the BEV fusion features generated by the channel attention mechanism, as well as the challenge of inadequate interaction between features. We further develop a BEV self-attention mechanism to apply global operations on the features. This paper evaluates the effectiveness of the Att-BEVFusion fusion algorithm on the nuScenes dataset, and the results demonstrate that the algorithm achieved 72.0% mean average precision (mAP) and 74.3% nuScenes detection score (NDS), with an advanced detection accuracy of 88.9% and 91.8% for single-item detection of automotive and pedestrian categories, respectively. Full article

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18 pages, 4398 KiB

Open AccessArticle

Adaptive Second-Order Sliding Mode Wheel Slip Control for Electric Vehicles with In-Wheel Motors

by Jinghao Bi, Yaozhen Han, Mingdong Hou and Changshun Wang

World Electr. Veh. J. 2024, 15(11), 538; https://doi.org/10.3390/wevj15110538 - 20 Nov 2024

Abstract

The influence of the external environment can reduce the braking performance of the electric vehicle (EV) with in-wheel motors (IWM). In this paper, an adaptive sliding mode wheel slip control method with a vehicle speed observer consideration is proposed, which enables the EV [...] Read more.

The influence of the external environment can reduce the braking performance of the electric vehicle (EV) with in-wheel motors (IWM). In this paper, an adaptive sliding mode wheel slip control method with a vehicle speed observer consideration is proposed, which enables the EV to accurately track the optimal slip ratio in various environments and improve braking performance. First, the braking system dynamics model is established by taking the EV with IWM as the study object. Second, a super-twisting sliding mode observer is used to estimate the vehicle speed, and a new adaptive second-order sliding mode controller is constructed to control the braking torque. Finally, co-simulation experiments are performed under different conditions based on Carsim and MATLAB/Simulink, and the proposed scheme is validated by comparison with three control methods. The experimental results show that the proposed scheme has better control performance, and both the safety and control quality of the EV is improved. Full article

(This article belongs to the Topic Advanced Electric Vehicle Technology, 2nd Volume)

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30 pages, 9854 KiB

Open AccessArticle

An Activity Network Design and Charging Facility Planning Model Considering the Influence of Uncertain Activities in a Game Framework

by Zechao Ma, Xiaoming Liu, Weiqiang Wang, Shangjiang Yang, Yuqi Yang, Yingjie Zhao, Hanqing Xia and Yuanrong Wang

World Electr. Veh. J. 2024, 15(11), 537; https://doi.org/10.3390/wevj15110537 - 20 Nov 2024

Abstract

In the planning of public charging facilities and the charging activity network of users, there is a decision-making conflict among three stakeholders: the government, charging station enterprises, and electric vehicle users. Previous studies have described the tripartite game relationship in a relatively simplistic [...] Read more.

In the planning of public charging facilities and the charging activity network of users, there is a decision-making conflict among three stakeholders: the government, charging station enterprises, and electric vehicle users. Previous studies have described the tripartite game relationship in a relatively simplistic manner, and when designing charging facility planning schemes, they did not consider scenarios where users’ choice preferences undergo continuous random changes. In order to reduce the impacts of queuing phenomenon and resource idleness on the three participants, we introduce a bilateral matching algorithm combined with the dynamic Huff model as a strategy for EV charging selection in the passenger flow problem based on the three-dimensional activity network of time–space–energy of users. Meanwhile, the Dirichlet distribution is utilized to control the selection preferences on the user side, constructing uncertain scenarios for the choice of user charging activities. In this study, we establish a bilevel programming model that takes into account the uncertainty in social responsibility and user charging selection behavior. Solutions for the activity network and facility planning schemes can be derived based on the collaborative relationships among the three parties. The model employs a robust optimization method to collaboratively design the charging activity network and facility planning scheme. For this mixed-integer nonlinear multi-objective multi-constraint optimization problem, the model is solved by the NSGA-II algorithm, and the optimal compromise scheme is determined by using the EWM-TOPSIS comprehensive evaluation method for the Pareto solution set. Finally, the efficacy of the model and the solution algorithm is illustrated by a simulation example in a real urban space. Full article

(This article belongs to the Special Issue Electric Vehicles and Charging Facilities for a Sustainable Transport Sector)

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22 pages, 3414 KiB

Open AccessArticle

Symmetrical Short-Circuit Behavior Prediction of Rare-Earth Permanent Magnet Synchronous Motors

by Fabian Eichin, Maarten Kamper, Stiaan Gerber and Rong-Jie Wang

World Electr. Veh. J. 2024, 15(11), 536; https://doi.org/10.3390/wevj15110536 - 19 Nov 2024

Abstract

Since the advent of rare-earth permanent magnet (PM) materials, PM synchronous machines (PMSMs) have become popular in power generation, industrial drives, and e-mobility. However, rare-earth PMs in PMSMs are prone to temperature- and operation-related irreversible demagnetization. Additionally, faults can endanger components like inverters, [...] Read more.

Since the advent of rare-earth permanent magnet (PM) materials, PM synchronous machines (PMSMs) have become popular in power generation, industrial drives, and e-mobility. However, rare-earth PMs in PMSMs are prone to temperature- and operation-related irreversible demagnetization. Additionally, faults can endanger components like inverters, batteries, and mechanical structures. Designing a fault-tolerant machine requires considering these risks during the PMSM design phase. Traditional transient finite element analysis is time-consuming, but fast analytical simulation methods provide viable alternatives. This paper evaluates methods for analyzing dynamic three-phase short-circuit (3PSC) events in PMSMs. Experimental measurements on a PMSM prototype serve as benchmarks. The results show that accounting for machine saturation reduces discrepancies between measured and predicted outcomes by 20%. While spatial harmonic content and sub-transient reactance can be neglected in some cases, caution is required in other scenarios. Eddy currents in larger machines significantly impact 3PSC dynamics. This work provides a quick assessment based on general machine parameters, improving fault-tolerant PMSM design. Full article

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14 pages, 10803 KiB

Open AccessArticle

Improvement on Electromagnetic Performance of Axial–Radial Flux Type Permanent Magnet Machines by Optimal Stator Slot Number

by Ran Yi, Chunwei Yuan, Hongbo Qiu, Wenhao Gao and Junyi Ren

World Electr. Veh. J. 2024, 15(11), 535; https://doi.org/10.3390/wevj15110535 - 19 Nov 2024

Abstract

To achieve the objective of high torque, a high utilization rate of PMs, and flexible flux regulation capability of the permanent magnet (PM) machine, an axial–radial flux type permanent magnet (ARFTPM) machine was studied in this paper. The working principle of the ARFTPM [...] Read more.

To achieve the objective of high torque, a high utilization rate of PMs, and flexible flux regulation capability of the permanent magnet (PM) machine, an axial–radial flux type permanent magnet (ARFTPM) machine was studied in this paper. The working principle of the ARFTPM machine is analyzed by illustrating the flux paths. Then, the influence of stator slot number on the flux regulation capability and torque is studied. A full comparison of the main parameters and electromagnetic performances of the ARFTPM machine with different stator slot numbers is presented, including winding coefficient, back electromotive force (EMF), cogging torque, average torque, and torque-angle characteristics. The optimal stator slot number was obtained. Finally, the 12-slot/10-pole prototype machine is manufactured and tested to validate the simulation data and theoretical analysis. Full article

(This article belongs to the Special Issue Advanced Electrical Machine and Power Electronics for the Charging and Drive System of Electric Vehicles (EVs))

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16 pages, 12639 KiB

Open AccessArticle

Study on the Crashworthiness of a Battery Frame Design for an Electric Vehicle Using FEM

by Adrian Daniel Muresanu, Mircea Cristian Dudescu and David Tica

World Electr. Veh. J. 2024, 15(11), 534; https://doi.org/10.3390/wevj15110534 - 19 Nov 2024

Abstract

This paper presents an optimized method for evaluating and enhancing the crashworthiness of an electric vehicle (EV) battery frame, leveraging finite element model (FEM) simulations with minimal computational effort. The study begins by utilizing a publicly available LS-DYNA model of a conventional Toyota [...] Read more.

This paper presents an optimized method for evaluating and enhancing the crashworthiness of an electric vehicle (EV) battery frame, leveraging finite element model (FEM) simulations with minimal computational effort. The study begins by utilizing a publicly available LS-DYNA model of a conventional Toyota Camry, simplifying it to include only the structures relevant to a side pole crash scenario. The crash simulations adhere to FMVSS214 and UNR135 standards, while also extending to higher speeds of 45 km/h to evaluate performance under more severe conditions. A dummy frame with virtual mass is integrated into the model to approximate the realistic center of gravity (COG) of an EV and to facilitate visualization. Based on the side pole crash results, critical parameters are extracted to inform the development of load cases for the EV battery. The proposed battery frame, constructed from aluminum, houses a representative volume of battery cells. These cells are defined through a homogenization process derived from individual and pack of cell crash tests. The crashworthiness of the battery frame is assessed by measuring the overall intrusion along the Y-axis and the specific intrusion into the representative volume. This method not only highlights the challenges of adapting conventional vehicle platforms for EVs or for dual compatibility with both conventional and electric powertrains but also provides a framework for developing and testing battery frames independently. By creating relevant load cases derived from full vehicle crash data, this approach enables battery frames to be optimized and evaluated as standalone components, offering a method for efficient and adaptable battery frame development. This approach provides a streamlined yet effective process for optimizing the crash performance of EV battery systems within existing vehicle platforms. Full article

(This article belongs to the Special Issue Electric Vehicle Crash Safety Design)

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30 pages, 22040 KiB

Open AccessArticle

Optimal Driving Torque Control Strategy for Front and Rear Independently Driven Electric Vehicles Based on Online Real-Time Model Predictive Control

by Hang Yin, Chao Ma, Haifeng Wang, Zhihao Sun and Kun Yang

World Electr. Veh. J. 2024, 15(11), 533; https://doi.org/10.3390/wevj15110533 - 18 Nov 2024

Abstract

This paper presents a novel driving torque control strategy for the front and rear independently driven electric vehicle (FRIDEV) to reduce energy consumption and enhance vehicle stability. The strategy is built on a comprehensive vehicle model that integrates vertical load transfer, tire slip [...] Read more.

This paper presents a novel driving torque control strategy for the front and rear independently driven electric vehicle (FRIDEV) to reduce energy consumption and enhance vehicle stability. The strategy is built on a comprehensive vehicle model that integrates vertical load transfer, tire slip dynamics, and an electric system model that accounts for losses in induction motors (IMs), permanent magnet synchronous motors (PMSMs), inverters, and batteries. The torque control problem is framed with a nonlinear model predictive control (MPC) method, utilizing state-space equations as representations of vehicle dynamics. The optimization targets adjust in real-time based on road traction conditions, with the slip rate of front and rear wheels determining the torque control strategy. Active slip control is applied when slip rates exceed critical thresholds, while under normal conditions, torque distribution is optimized to minimize energy losses. To enable online real-time implementation, an improved sparrow search algorithm (SSA) is designed. Simulations in MATLAB/Simulink confirm that the proposed online strategy reduces energy consumption by 2.3% under the China light-duty vehicle test cycle-passenger cars (CLTC-P) compared to a rule-based strategy. Under low-adhesion conditions, the proposed online strategy effectively manages slip ratios, ensuring stability and performance. Improved SSA also enhances computational efficiency by approximately 44%–52%, making the online strategy viable for real-time applications. Full article

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18 pages, 3827 KiB

Open AccessArticle

Adaptive Joint Sigma-Point Kalman Filtering for Lithium-Ion Battery Parameters and State-of-Charge Estimation

by Houda Bouchareb, Khadija Saqli, Nacer Kouider M’sirdi and Mohammed Oudghiri Bentaie

World Electr. Veh. J. 2024, 15(11), 532; https://doi.org/10.3390/wevj15110532 - 18 Nov 2024

Abstract

Precise modeling and state of charge (SoC) estimation of a lithium-ion battery (LIB) are crucial for the safety and longevity of battery systems in electric vehicles. Traditional methods often fail to adapt to the dynamic, nonlinear, and time-varying behavior of LIBs under different [...] Read more.

Precise modeling and state of charge (SoC) estimation of a lithium-ion battery (LIB) are crucial for the safety and longevity of battery systems in electric vehicles. Traditional methods often fail to adapt to the dynamic, nonlinear, and time-varying behavior of LIBs under different operating conditions. In this paper, an advanced joint estimation approach of the model parameters and SoC is proposed utilizing an enhanced Sigma Point Kalman Filter (SPKF). Based on the second-order equivalent circuit model (2RC-ECM), the proposed approach was compared to the two most widely used methods for simultaneously estimating the model parameters and SoC, including a hybrid recursive least square (RLS)-extended Kalman filter (EKF) method, and simple joint SPKF. The proposed adaptive joint SPKF (ASPKF) method addresses the limitations of both the RLS+EKF and simple joint SPKF, especially under dynamic operating conditions. By dynamically adjusting to changes in the battery’s characteristics, the method significantly enhances model accuracy and performance. The results demonstrate the robustness, computational efficiency, and reliability of the proposed ASPKF approach compared to traditional methods, making it an ideal solution for battery management systems (BMS) in modern EVs. Full article

(This article belongs to the Special Issue Lithium-Ion Battery Diagnosis: Health and Safety)

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13 pages, 497 KiB

Open AccessArticle

Path Planning for Unmanned Aerial Vehicles in Dynamic Environments: A Novel Approach Using Improved A* and Grey Wolf Optimizer

by Ali Haidar Ahmad, Oussama Zahwe, Abbass Nasser and Benoit Clement

World Electr. Veh. J. 2024, 15(11), 531; https://doi.org/10.3390/wevj15110531 - 18 Nov 2024

Abstract

Unmanned aerial vehicles (UAVs) play pivotal roles in various applications, from surveillance to delivery services. Efficient path planning for UAVs in dynamic environments with obstacles and moving landing stations is essential to ensure safe and reliable operations. In this study, we propose a [...] Read more.

Unmanned aerial vehicles (UAVs) play pivotal roles in various applications, from surveillance to delivery services. Efficient path planning for UAVs in dynamic environments with obstacles and moving landing stations is essential to ensure safe and reliable operations. In this study, we propose a novel approach that combines the A* algorithm with the grey wolf optimizer (GWO) for path planning, referred to as GW-A*. Our approach enhances the traditional A algorithm by incorporating weighted nodes, where the weights are determined based on the distance from obstacles and further optimized using GWO. A simulation using dynamic factors such as wind direction and wind speed, which affect the quadrotor UAV in the presence of obstacles, was used to test the new approach, and we compared it with the A* algorithm using various heuristics. The results showed that GW-A* outperformed A* in most scenarios with high and low wind speeds, offering more efficient paths and greater adaptability. Full article

(This article belongs to the Special Issue Research on Intelligent Vehicle Path Planning Algorithm)

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15 pages, 1478 KiB

Open AccessArticle

Tapping the Brakes: An Exploratory Survey of Consumers’ Perceptions of Autonomous Vehicles

by George D. Shows, Mathew Zothner and Pia A. Albinsson

World Electr. Veh. J. 2024, 15(11), 530; https://doi.org/10.3390/wevj15110530 - 18 Nov 2024

Abstract

The purpose of this study is to gain a better understanding of the difficulty in measuring consumer acceptance of emergent technologies where artificial intelligence is present in autonomous vehicles (AVs). Using the Technology Acceptance Model (TAM) as our theoretical lens, survey data of [...] Read more.

The purpose of this study is to gain a better understanding of the difficulty in measuring consumer acceptance of emergent technologies where artificial intelligence is present in autonomous vehicles (AVs). Using the Technology Acceptance Model (TAM) as our theoretical lens, survey data of US adult consumers are used to better understand consumer acceptance of AVs. Results from Partial Least Squares–Structural Equation Modeling (PLS-SEM) show that the certainty of product performance and interest are positively related to usage. Surprisingly, the relationship between two variables, internal locus of control and ease of use and usage, was not significant, which could be explained by AVs being self-driving and the ease of use therefore not being important in this context. Internal locus of control was negatively related to willingness to buy, and interest and usage were positively related to willingness to buy. Mediation analysis further explains these relationships. This research calls into question the TAM, long used as a measurement for the acceptance of information systems, as an acceptable model for measuring consumer acceptance where the intent is to purchase technology that contains artificial intelligence. Full article

(This article belongs to the Special Issue Advancements in Autonomous Vehicles: Security, Optimization and Future Challenges)

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25 pages, 11758 KiB

Open AccessArticle

Research on the Smooth Switching Control Strategy of Electric Vehicle Charging Stations Based on Photovoltaic–Storage–Charging Integration

by Tao Wang, Jinghao Ma, Cunhao Lin, Xin Li, Shenhui Chen and Jihui Zhang

World Electr. Veh. J. 2024, 15(11), 528; https://doi.org/10.3390/wevj15110528 - 17 Nov 2024

Abstract

To facilitate seamless transitions between grid-connected and islanded modes in PV–storage–charging integration, an energy storage system converter is designated as the subject of investigation, and its operational principles are examined. Feed-forward decoupling, double closed-loop, constant-power (PQ), constant-voltage–constant-frequency (V/F), and constant-voltage charge and discharge [...] Read more.

To facilitate seamless transitions between grid-connected and islanded modes in PV–storage–charging integration, an energy storage system converter is designated as the subject of investigation, and its operational principles are examined. Feed-forward decoupling, double closed-loop, constant-power (PQ), constant-voltage–constant-frequency (V/F), and constant-voltage charge and discharge control strategies are developed. The PQ and V/F control framework of the energy storage battery comprises an enhanced common current inner loop and a switching voltage outer loop. The current reference value output by the voltage outer loop and the voltage signal output by the current inner loop are compensated. The transient impact is reduced, and the smooth switching of the microgrid from the grid-connected mode to the island mode is realized, which significantly improves the power quality and ensures the uninterrupted charging of electric vehicles and the stable operation of the key load of the system. By constructing a simulation model of the photovoltaic energy storage microgrid on the MATLAB/Simulink platform, the practicability of the control strategy proposed in this paper is verified. Full article

(This article belongs to the Special Issue Intelligent Electric Vehicle Control, Testing and Evaluation)

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14 pages, 3119 KiB

Open AccessArticle

An Adaptive Cruise Control Strategy for Intelligent Vehicles Based on Hierarchical Control

by Di Hu, Jingbo Zhao, Jianfeng Zheng and Haimei Liu

World Electr. Veh. J. 2024, 15(11), 529; https://doi.org/10.3390/wevj15110529 - 15 Nov 2024

Abstract

To minimize the occurrence of traffic accidents, such as vehicle rear-end collisions, while enhancing vehicle following, stability, economy, and ride comfort, a hierarchical adaptive cruise control strategy for vehicles is proposed. The upper-level controller computes the desired vehicle output acceleration based on model [...] Read more.

To minimize the occurrence of traffic accidents, such as vehicle rear-end collisions, while enhancing vehicle following, stability, economy, and ride comfort, a hierarchical adaptive cruise control strategy for vehicles is proposed. The upper-level controller computes the desired vehicle output acceleration based on model predictive control and switches between speed and spacing control in accordance with driving conditions. The brake/throttle opening switching model, brake control inverse model, and throttle opening inverse model in the lower-level controller of ACC are designed to obtain the desired throttle opening and braking pressure of the vehicle, thereby achieving control of the vehicle. A joint simulation platform was established using PreScan, CarSim and Matlab/Simulink. Finally, simulations for three typical working conditions were conducted in Simulink to verify the performance of the adaptive cruise control strategy. The results indicate that, in both the constant-speed cruise and vehicle-following cruise conditions, the vehicle can rapidly and stably follow the set initial speed and consistently maintain a safe distance from the preceding vehicle. Under the emergency braking condition, the vehicle can promptly respond with deceleration, ensuring driving safety. The proposed control strategy can accurately and safely track the target vehicle in diverse driving conditions and can concurrently fulfill the requirements of economy and comfort during vehicle travel. Full article

(This article belongs to the Special Issue Recent Advances in Intelligent Vehicle)

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13 pages, 2762 KiB

Open AccessArticle

Advanced Point Cloud Techniques for Improved 3D Object Detection: A Study on DBSCAN, Attention, and Downsampling

by Wenqiang Zhang, Xiang Dong, Jingjing Cheng and Shuo Wang

World Electr. Veh. J. 2024, 15(11), 527; https://doi.org/10.3390/wevj15110527 - 15 Nov 2024

Abstract

To address the challenges of limited detection precision and insufficient segmentation of small to medium-sized objects in dynamic and complex scenarios, such as the dense intermingling of pedestrians, vehicles, and various obstacles in urban environments, we propose an enhanced methodology. Firstly, we integrated [...] Read more.

To address the challenges of limited detection precision and insufficient segmentation of small to medium-sized objects in dynamic and complex scenarios, such as the dense intermingling of pedestrians, vehicles, and various obstacles in urban environments, we propose an enhanced methodology. Firstly, we integrated a point cloud processing module utilizing the DBSCAN clustering algorithm to effectively segment and extract critical features from the point cloud data. Secondly, we introduced a fusion attention mechanism that significantly improves the network’s capability to capture both global and local features, thereby enhancing object detection performance in complex environments. Finally, we incorporated a CSPNet downsampling module, which substantially boosts the network’s overall performance and processing speed while reducing computational costs through advanced feature map segmentation and fusion techniques. The proposed method was evaluated using the KITTI dataset. Under moderate difficulty, the BEV mAP for detecting cars, pedestrians, and cyclists achieved 87.74%, 55.07%, and 67.78%, reflecting improvements of 1.64%, 5.84%, and 5.53% over PointPillars. For 3D mAP, the detection accuracy for cars, pedestrians, and cyclists reached 77.90%, 49.22%, and 62.10%, with improvements of 2.91%, 5.69%, and 3.03% compared to PointPillars. Full article

(This article belongs to the Special Issue Recent Advances in Intelligent Vehicle)

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18 pages, 980 KiB

Open AccessArticle

Leveraging Six Values for Company Performance: Adaptation of Sustainable Business Model Innovation Strategies in Chinese Electric Vehicle Brand Enterprises

by Xiaohui Zang, Raja Nazim Abdullah, Long Li and Ibiwani Alisa Hussain

World Electr. Veh. J. 2024, 15(11), 526; https://doi.org/10.3390/wevj15110526 - 15 Nov 2024

Abstract

Business model innovation is crucial for enhancing company performance. This study aims to investigate the relationship between the six dimensions of sustainable business model innovation and company performance among Chinese electric vehicle brands. A structural equation model is constructed based on a comprehensive [...] Read more.

Business model innovation is crucial for enhancing company performance. This study aims to investigate the relationship between the six dimensions of sustainable business model innovation and company performance among Chinese electric vehicle brands. A structural equation model is constructed based on a comprehensive literature review and hypothesis development. Using PLS-SEM, this study empirically analyzes questionnaire data collected from the top 12 electric vehicle brands in China to explore the relationship between these six core dimensions and company performance. The results indicate that innovation in “value proposition to customers”, value creation, value delivery, and “value of residual” have a significantly positive impact on the performance of Chinese electric vehicle brands. However, value capture innovation and “value of after-sales service” innovation were not found to be statistically significant. This paper provides an in-depth analysis of the mechanism through which sustainable business model innovation impacts company performance, enriching the theoretical foundation of academic research in this field and broadening its practical applications in management. Full article

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