With the advancement of machine-learning and deep-learning technologies, the estimation of the state of charge (SOC) of lithium-ion batteries is gradually shifting from traditional methodologies to a new generation of digital and AI-driven data-centric approaches. This paper provides a comprehensive review of the three main steps involved in various machine-learning-based SOC estimation methods. It delves into the aspects of data collection and preparation, model selection and training, as well as model evaluation and optimization, offering a thorough analysis, synthesis, and summary. The aim is to lower the research barrier for professionals in the field and contribute to the advancement of intelligent SOC estimation in the battery domain.
{"title":"A Review of Lithium-Ion Battery State of Charge Estimation Methods Based on Machine Learning","authors":"Feng Zhao, Yun Guo, Baoming Chen","doi":"10.3390/wevj15040131","DOIUrl":"https://doi.org/10.3390/wevj15040131","url":null,"abstract":"With the advancement of machine-learning and deep-learning technologies, the estimation of the state of charge (SOC) of lithium-ion batteries is gradually shifting from traditional methodologies to a new generation of digital and AI-driven data-centric approaches. This paper provides a comprehensive review of the three main steps involved in various machine-learning-based SOC estimation methods. It delves into the aspects of data collection and preparation, model selection and training, as well as model evaluation and optimization, offering a thorough analysis, synthesis, and summary. The aim is to lower the research barrier for professionals in the field and contribute to the advancement of intelligent SOC estimation in the battery domain.","PeriodicalId":38979,"journal":{"name":"World Electric Vehicle Journal","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2024-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140382473","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The increasing level of intelligence in automobiles is driving a shift in the human–machine relationship. Users are paying more attention to the intelligent cabin and showing a tendency toward customization. As culture is considered to be an important factor in guiding user behavior and preference, this study innovatively incorporates cultural and human factors into the model to understand how individual cultural orientation influences user preference for innovative human-machine interaction (HMI) features. Firstly, this study considered five Hofstede cultural dimensions as potential impact factors and constructed a prediction model through the random forest algorithm so as to analyze the influence mechanism of culture. Subsequently, K-means clustering was used to classify the sample into three user groups and then predict their preferences for the innovative features in the intelligent cabin. The results showed that users with a higher power distance index preferred a sense of ceremony and show-off-related features such as ambient lighting and welcome mode, whereas users with high individualism were keen on a more open and personalized in-vehicle information system. Long-term orientation was found to be associated with features that help to improve efficiency, and users with a lower level of uncertainty avoidance and restraint were more likely to be attracted to new features and were also more willing to use entertainment-related features. The methodology developed in this study can be widely applied to people in different countries, thus effectively exploring the personal requirements of different individuals, guiding further user experience design and localization when breaking into a new market.
{"title":"Predicting User Preference for Innovative Features in Intelligent Connected Vehicles from a Cultural Perspective","authors":"Jun Ma, Yuqi Gong, Wenxia Xu","doi":"10.3390/wevj15040130","DOIUrl":"https://doi.org/10.3390/wevj15040130","url":null,"abstract":"The increasing level of intelligence in automobiles is driving a shift in the human–machine relationship. Users are paying more attention to the intelligent cabin and showing a tendency toward customization. As culture is considered to be an important factor in guiding user behavior and preference, this study innovatively incorporates cultural and human factors into the model to understand how individual cultural orientation influences user preference for innovative human-machine interaction (HMI) features. Firstly, this study considered five Hofstede cultural dimensions as potential impact factors and constructed a prediction model through the random forest algorithm so as to analyze the influence mechanism of culture. Subsequently, K-means clustering was used to classify the sample into three user groups and then predict their preferences for the innovative features in the intelligent cabin. The results showed that users with a higher power distance index preferred a sense of ceremony and show-off-related features such as ambient lighting and welcome mode, whereas users with high individualism were keen on a more open and personalized in-vehicle information system. Long-term orientation was found to be associated with features that help to improve efficiency, and users with a lower level of uncertainty avoidance and restraint were more likely to be attracted to new features and were also more willing to use entertainment-related features. The methodology developed in this study can be widely applied to people in different countries, thus effectively exploring the personal requirements of different individuals, guiding further user experience design and localization when breaking into a new market.","PeriodicalId":38979,"journal":{"name":"World Electric Vehicle Journal","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2024-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140384606","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The utilization of photovoltaic (PV) generation to charge storage batteries in recreational vehicles (RVs) is becoming increasingly prevalent. However, the performance of PV generation systems is hindered by the mismatch caused by different module types and varying environmental conditions. This discrepancy negatively impacts the output performance of PV modules, resulting in reduced system efficiency. To address this issue, this paper explored the series–parallel output characteristics of different types of PV modules and summarized the methods for configuring PV modules in a mixed-structure PV generation system for RV energy supplementation. Building upon this foundation, a novel equalization scheme based on extremum-seeking control (ESC) is introduced. The scheme initially employs a forward–flyback converter (FFC) to equalize the current among series-connected PV modules, followed by matching the voltage between parallel-connected PV module strings. Finally, the ESC is utilized to optimize the real-time output power of the PV generation system, thereby enhancing overall system efficiency. Through simulation experiments conducted on a PV generation system with four types of mixed-connection PV modules employing the PLECS simulation platform, simulated results demonstrate the effectiveness of the proposed scheme in improving PV module output performance and maximum power tracking efficiency. The simulation data reveal that the proposed scheme achieves an impressive average tracking efficiency of 99.15%, surpassing the efficiency of the global maximum power point tracking scheme based on an enhanced perturb and observe algorithm.
{"title":"Power Optimization of Multi-Type Mixed-Connection Photovoltaic Generation System for Recreational Vehicles","authors":"DaiBin Tang, F. Siaw, Tzer Hwai Gilbert Thio","doi":"10.3390/wevj15040125","DOIUrl":"https://doi.org/10.3390/wevj15040125","url":null,"abstract":"The utilization of photovoltaic (PV) generation to charge storage batteries in recreational vehicles (RVs) is becoming increasingly prevalent. However, the performance of PV generation systems is hindered by the mismatch caused by different module types and varying environmental conditions. This discrepancy negatively impacts the output performance of PV modules, resulting in reduced system efficiency. To address this issue, this paper explored the series–parallel output characteristics of different types of PV modules and summarized the methods for configuring PV modules in a mixed-structure PV generation system for RV energy supplementation. Building upon this foundation, a novel equalization scheme based on extremum-seeking control (ESC) is introduced. The scheme initially employs a forward–flyback converter (FFC) to equalize the current among series-connected PV modules, followed by matching the voltage between parallel-connected PV module strings. Finally, the ESC is utilized to optimize the real-time output power of the PV generation system, thereby enhancing overall system efficiency. Through simulation experiments conducted on a PV generation system with four types of mixed-connection PV modules employing the PLECS simulation platform, simulated results demonstrate the effectiveness of the proposed scheme in improving PV module output performance and maximum power tracking efficiency. The simulation data reveal that the proposed scheme achieves an impressive average tracking efficiency of 99.15%, surpassing the efficiency of the global maximum power point tracking scheme based on an enhanced perturb and observe algorithm.","PeriodicalId":38979,"journal":{"name":"World Electric Vehicle Journal","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2024-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140216309","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mahipal Bukya, Bhukya Padma, Rajesh Kumar, A. Mathur, N. Prasad
As the adoption of electric vehicles (EVs) continues to rise, attention has switched to ensuring the safety of EV operations. The exponential growth in battery technology over the past several years has changed the face of energy storage and sparked a revolution in several industries. The degradation of battery insulation during regular use is a significant concern. The high voltage (HV) and current levels in HV electric vehicles pose a significant electrical threat.The advancement of electric vehicle technology has led to an increasing presence of HV electric equipment throughout the vehicle. The insulation strength and early health status detection of the batteries are essential in ensuring safety in EVs. This paper studies the different insulation detection techniques and the development of adaptive filter (AF) algorithms based on field-programmable gate arrays (FPGAs) for insulation detection. FPGAs are amongst the most accurate and fast detection techniques among all the insulation detection techniques used so far in electric vehicles. This study proposes an FPGA-based VFF-RLS algorithm for effectively implementing insulation detection in EVs. The experimental test results using FPGAs demonstrate that the proposed method can rapidly monitor changes in insulation resistance (IR). The VFFRLS-based FPGA technique works sufficiently well to reduce errors when dealing with variations in voltage and resistance conditions at the battery terminals.
{"title":"FPGA-Based VFF-RLS Algorithm for Battery Insulation Detection in Electric Vehicles","authors":"Mahipal Bukya, Bhukya Padma, Rajesh Kumar, A. Mathur, N. Prasad","doi":"10.3390/wevj15040129","DOIUrl":"https://doi.org/10.3390/wevj15040129","url":null,"abstract":"As the adoption of electric vehicles (EVs) continues to rise, attention has switched to ensuring the safety of EV operations. The exponential growth in battery technology over the past several years has changed the face of energy storage and sparked a revolution in several industries. The degradation of battery insulation during regular use is a significant concern. The high voltage (HV) and current levels in HV electric vehicles pose a significant electrical threat.The advancement of electric vehicle technology has led to an increasing presence of HV electric equipment throughout the vehicle. The insulation strength and early health status detection of the batteries are essential in ensuring safety in EVs. This paper studies the different insulation detection techniques and the development of adaptive filter (AF) algorithms based on field-programmable gate arrays (FPGAs) for insulation detection. FPGAs are amongst the most accurate and fast detection techniques among all the insulation detection techniques used so far in electric vehicles. This study proposes an FPGA-based VFF-RLS algorithm for effectively implementing insulation detection in EVs. The experimental test results using FPGAs demonstrate that the proposed method can rapidly monitor changes in insulation resistance (IR). The VFFRLS-based FPGA technique works sufficiently well to reduce errors when dealing with variations in voltage and resistance conditions at the battery terminals.","PeriodicalId":38979,"journal":{"name":"World Electric Vehicle Journal","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2024-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140387226","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Weizhen Zhu, Yuhao Zhang, W. Kong, Fachao Jiang, Pengxiao Ji
This article aims to address the unnecessary stopping and low efficiency issues present in existing multi-machine cooperative steering control methods. To tackle this challenge, a novel cooperative control approach for multiple agricultural machines is proposed, considering two typical steering modes of farm machinery. This approach encompasses a multi-machine cooperative control framework suitable for both steering modes. Based on the established lateral and longitudinal kinematics models of the farm machines, the method includes a path-tracking controller designed using the pure pursuit and Stanley algorithms, a formation-keeping controller based on PID control, and a T-turn cooperative-steering controller based on a problem-solving approach. To assess the method’s viability, a collaborative simulation platform utilizing CarSim and Simulink was constructed, which conducted simulations for both U-turn and T-turn cooperative steering controls. The simulation results indicate that the proposed control framework and methodology can effectively ensure no collision risk during the U-turn and T-turn cooperative steering processes for three farm machines, eliminating stopping in T-turn, enhancing safety, and improving fuel economy. Compared with traditional sequential control methods, the proposed approach reduced operation time by 17.47 s and increased efficiency by 15.29% in the same scenarios.
本文旨在解决现有多机协同转向控制方法中存在的不必要停车和低效率问题。为应对这一挑战，考虑到农用机械的两种典型转向模式，提出了一种新型的多农用机械协同控制方法。该方法包含一个适用于两种转向模式的多机协同控制框架。基于已建立的农机横向和纵向运动学模型，该方法包括使用纯粹追寻和斯坦利算法设计的路径跟踪控制器、基于 PID 控制的编队保持控制器，以及基于问题解决方法的 T 形转弯合作转向控制器。为了评估该方法的可行性，利用 CarSim 和 Simulink 构建了一个协同仿真平台，对 U 形转弯和 T 形转弯协同转向控制进行了仿真。仿真结果表明，所提出的控制框架和方法能有效确保三台农机在掉头和 T 形转弯协同转向过程中无碰撞风险，消除 T 形转弯中的停车现象，提高安全性和燃油经济性。与传统的顺序控制方法相比，所提出的方法在相同场景下减少了 17.47 秒的操作时间，提高了 15.29% 的效率。
{"title":"A Versatile Control Method for Multi-Agricultural Machine Cooperative Steering Applicable to Two Steering Modes","authors":"Weizhen Zhu, Yuhao Zhang, W. Kong, Fachao Jiang, Pengxiao Ji","doi":"10.3390/wevj15040126","DOIUrl":"https://doi.org/10.3390/wevj15040126","url":null,"abstract":"This article aims to address the unnecessary stopping and low efficiency issues present in existing multi-machine cooperative steering control methods. To tackle this challenge, a novel cooperative control approach for multiple agricultural machines is proposed, considering two typical steering modes of farm machinery. This approach encompasses a multi-machine cooperative control framework suitable for both steering modes. Based on the established lateral and longitudinal kinematics models of the farm machines, the method includes a path-tracking controller designed using the pure pursuit and Stanley algorithms, a formation-keeping controller based on PID control, and a T-turn cooperative-steering controller based on a problem-solving approach. To assess the method’s viability, a collaborative simulation platform utilizing CarSim and Simulink was constructed, which conducted simulations for both U-turn and T-turn cooperative steering controls. The simulation results indicate that the proposed control framework and methodology can effectively ensure no collision risk during the U-turn and T-turn cooperative steering processes for three farm machines, eliminating stopping in T-turn, enhancing safety, and improving fuel economy. Compared with traditional sequential control methods, the proposed approach reduced operation time by 17.47 s and increased efficiency by 15.29% in the same scenarios.","PeriodicalId":38979,"journal":{"name":"World Electric Vehicle Journal","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2024-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140387316","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mariana de F. Ramos, Dener A. L. Brandão, Diogo P. V. Galo, B. C. Cardoso Filho, I. Pires, T. Maia
This work presents a study of the performance of prime mover and hydraulic implement electrification in a backhoe loader. The results are validated through simulation and experimental tests. The construction and agriculture sector has grown in recent years with the aid of compact non-road mobile machines. However, as is common in fossil fuel-powered vehicles, they significantly contribute to increasing emissions. Previous research has primarily relied on powertrain electrification to address the low-efficiency drawbacks. Notably, compact off-road vehicles comprise implements less discussed in the literature. A hybrid series topology is employed, where the rear implement is driven by an electrical drive and the Diesel engine is coupled to a generator. A rule-based energy management strategy is applied. The operation of the Diesel engine and electrical machines in optimal points of the efficiency maps are the basis of the analysis. The design is validated using simulations and experimental tests in a commercial backhoe loader as a benchmark. Experimental and simulation results obtained from the hybrid series backhoe loader applied to the hydraulic implement show a 33% reduction in fuel consumption, demonstrating the effectiveness of electrification in reducing emissions and fuel consumption of compact non-road mobile machines.
{"title":"A Study on the Performance of the Electrification of Hydraulic Implements in a Compact Non-Road Mobile Machine: A Case Applied to a Backhoe Loader","authors":"Mariana de F. Ramos, Dener A. L. Brandão, Diogo P. V. Galo, B. C. Cardoso Filho, I. Pires, T. Maia","doi":"10.3390/wevj15040127","DOIUrl":"https://doi.org/10.3390/wevj15040127","url":null,"abstract":"This work presents a study of the performance of prime mover and hydraulic implement electrification in a backhoe loader. The results are validated through simulation and experimental tests. The construction and agriculture sector has grown in recent years with the aid of compact non-road mobile machines. However, as is common in fossil fuel-powered vehicles, they significantly contribute to increasing emissions. Previous research has primarily relied on powertrain electrification to address the low-efficiency drawbacks. Notably, compact off-road vehicles comprise implements less discussed in the literature. A hybrid series topology is employed, where the rear implement is driven by an electrical drive and the Diesel engine is coupled to a generator. A rule-based energy management strategy is applied. The operation of the Diesel engine and electrical machines in optimal points of the efficiency maps are the basis of the analysis. The design is validated using simulations and experimental tests in a commercial backhoe loader as a benchmark. Experimental and simulation results obtained from the hybrid series backhoe loader applied to the hydraulic implement show a 33% reduction in fuel consumption, demonstrating the effectiveness of electrification in reducing emissions and fuel consumption of compact non-road mobile machines.","PeriodicalId":38979,"journal":{"name":"World Electric Vehicle Journal","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2024-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140219075","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The three-phase voltage type Pulse Width Modulation (PWM) rectifier is widely used in the front-end power factor of electric vehicle wireless charging systems due to its simple control structure and easy implementation. The system often adopts a double closed-loop PI control method based on voltage and current, which inevitably leads to a significant starting current surge and poses significant risks to the safe operation of the equipment. On the basis of establishing a mathematical model for PWM rectifiers, this article analyzes in detail the causes of starting over-current and designs a starting strategy with a voltage outer proportional and integral separated active current directly given. Simulation experiments show that this method can reduce the starting over-current of PWM rectifiers and the excessive DC voltage surge towards normal operation during the starting process.
三相电压型脉宽调制（PWM）整流器因其控制结构简单、易于实现而被广泛应用于电动汽车无线充电系统的前端功率因数。该系统通常采用基于电压和电流的双闭环 PI 控制方法，这不可避免地会导致启动电流大幅骤增，给设备的安全运行带来极大风险。本文在建立 PWM 整流器数学模型的基础上，详细分析了起动过流的原因，并设计了直接给出电压外比例和积分分离有功电流的起动策略。仿真实验表明，这种方法可以减少 PWM 整流器的启动过电流，并降低启动过程中过高的直流电压浪涌，使其趋于正常运行。
{"title":"Suppression Strategy of Starting Current Impulse in the Front Stage Rectifier of Electric Vehicle WPT System","authors":"Guangye Li, Shouming Lv, Renming Yang","doi":"10.3390/wevj15040124","DOIUrl":"https://doi.org/10.3390/wevj15040124","url":null,"abstract":"The three-phase voltage type Pulse Width Modulation (PWM) rectifier is widely used in the front-end power factor of electric vehicle wireless charging systems due to its simple control structure and easy implementation. The system often adopts a double closed-loop PI control method based on voltage and current, which inevitably leads to a significant starting current surge and poses significant risks to the safe operation of the equipment. On the basis of establishing a mathematical model for PWM rectifiers, this article analyzes in detail the causes of starting over-current and designs a starting strategy with a voltage outer proportional and integral separated active current directly given. Simulation experiments show that this method can reduce the starting over-current of PWM rectifiers and the excessive DC voltage surge towards normal operation during the starting process.","PeriodicalId":38979,"journal":{"name":"World Electric Vehicle Journal","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2024-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140211643","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Further advances in hardware and software features are needed to optimize battery and thermal management systems to allow for the execution of longer trips in electric vehicles. This paper assesses the economic and environmental impacts of the following features: eco-charging, eco-driving, smart fast charging, predictive thermal powertrain and cabin conditioning, and an advanced heat pump system. A Total Cost of Ownership (TCO) and externalities calculation is carried out on two passenger cars and one light commercial vehicle (LCV). The energy consumption data from the vehicles are based on experiments. The analysis shows more benefits for the LCV, while the smart fast-charging feature on the car shows a slight increase in TCO. However, negative results did not contribute significantly compared to the ability to install a smaller battery capacity for similar use.
{"title":"Economic and Environmental Assessment of Technologies Optimizing the Execution of Long Trips for Electric Vehicles","authors":"Léa D’amore, Daniele Costa, M. Messagie","doi":"10.3390/wevj15040128","DOIUrl":"https://doi.org/10.3390/wevj15040128","url":null,"abstract":"Further advances in hardware and software features are needed to optimize battery and thermal management systems to allow for the execution of longer trips in electric vehicles. This paper assesses the economic and environmental impacts of the following features: eco-charging, eco-driving, smart fast charging, predictive thermal powertrain and cabin conditioning, and an advanced heat pump system. A Total Cost of Ownership (TCO) and externalities calculation is carried out on two passenger cars and one light commercial vehicle (LCV). The energy consumption data from the vehicles are based on experiments. The analysis shows more benefits for the LCV, while the smart fast-charging feature on the car shows a slight increase in TCO. However, negative results did not contribute significantly compared to the ability to install a smaller battery capacity for similar use.","PeriodicalId":38979,"journal":{"name":"World Electric Vehicle Journal","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2024-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140217502","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Data acquisition from a vehicle operating in real driving conditions is extremely useful for analyzing the real-time behavior of the vehicle and its components. A few studies have measured the real-time data for a four-wheeler electric vehicle. However, no attempts have been reported to measure the real-time data and find the inverter efficiency for a two-wheeler electric vehicle. The present work has accomplished successful real-time data acquisition from a two-wheeler electric vehicle. The real-time current and voltage coming in and going out from the inverter, frequency of the motor operation, power factor, distance covered, and velocity have been measured. The inverter efficiency is found to be over 95% for over 80% of the total drive time, and the power factor for the motor is over 0.8 for almost 50% of the total drive time. A few insights on driver behavior and finally the torque-speed characteristics and two quadrant operation of the motor are discussed.
{"title":"Data Acquisition and Performance Analysis during Real-Time Driving of a Two-Wheeler Electric Vehicle—A Case Study","authors":"Divyakumar Bhavsar, Ramesh Kaipakam Jaychandra, Mayank Mittal","doi":"10.3390/wevj15030121","DOIUrl":"https://doi.org/10.3390/wevj15030121","url":null,"abstract":"Data acquisition from a vehicle operating in real driving conditions is extremely useful for analyzing the real-time behavior of the vehicle and its components. A few studies have measured the real-time data for a four-wheeler electric vehicle. However, no attempts have been reported to measure the real-time data and find the inverter efficiency for a two-wheeler electric vehicle. The present work has accomplished successful real-time data acquisition from a two-wheeler electric vehicle. The real-time current and voltage coming in and going out from the inverter, frequency of the motor operation, power factor, distance covered, and velocity have been measured. The inverter efficiency is found to be over 95% for over 80% of the total drive time, and the power factor for the motor is over 0.8 for almost 50% of the total drive time. A few insights on driver behavior and finally the torque-speed characteristics and two quadrant operation of the motor are discussed.","PeriodicalId":38979,"journal":{"name":"World Electric Vehicle Journal","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2024-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140222046","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A position estimation method for unmanned tracked vehicles based on a steering dynamics model was developed during this study. This method can be used to estimate the position of a tracked vehicle in real time without relying on a high-precision positioning system. First, the relationship between the shear displacement of the track relative to the ground and the speed and yaw rate of the tracked vehicle during the steering process was analyzed. Next, the steering force of the tracked vehicle was calculated by using the shear force–displacement theory, and a steering dynamics model considering the acceleration of the vehicle was established. The experimental results show that this steering dynamics model produced more accurate position estimations for an unmanned tracked vehicle than did the kinematics model. This method can serve as a reference for the positioning of unmanned tracked vehicles working in special environments that cannot use precise positioning systems.
{"title":"Position Estimation Method for Unmanned Tracked Vehicles Based on a Steering Dynamics Model","authors":"Weijian Jia, Xixia Liu, Chuanqing Zhang, Dabing Xue, Shaoliang Zhang","doi":"10.3390/wevj15030120","DOIUrl":"https://doi.org/10.3390/wevj15030120","url":null,"abstract":"A position estimation method for unmanned tracked vehicles based on a steering dynamics model was developed during this study. This method can be used to estimate the position of a tracked vehicle in real time without relying on a high-precision positioning system. First, the relationship between the shear displacement of the track relative to the ground and the speed and yaw rate of the tracked vehicle during the steering process was analyzed. Next, the steering force of the tracked vehicle was calculated by using the shear force–displacement theory, and a steering dynamics model considering the acceleration of the vehicle was established. The experimental results show that this steering dynamics model produced more accurate position estimations for an unmanned tracked vehicle than did the kinematics model. This method can serve as a reference for the positioning of unmanned tracked vehicles working in special environments that cannot use precise positioning systems.","PeriodicalId":38979,"journal":{"name":"World Electric Vehicle Journal","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2024-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140223542","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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