Hamza Touhs, Anas Temouden, A. Khallaayoun, Mhammed Chraibi, Hamza El Hafdaoui
This research delves into the intricate landscape of energy scheduling and optimization within microgrid and residential contexts, addressing pivotal aspects such as real-time scheduling systems, challenges in dynamic pricing, and an array of optimization strategies. This paper introduces a cutting-edge scheduling algorithm, harnessing the power of artificial neural networks driven by Long Short-Term Memory Networks, and highlights its exceptional performance, boasting a significantly lower Mean Absolute Error of 5.32 compared to conventional models. This heightened predictive accuracy translates into tangible improvements in both energy efficiency and cost savings. This study underscores the delicate balance between user satisfaction, cost reduction, and efficient scheduling for sustainable energy consumption, showcasing a remarkable 38% enhancement in optimized schedules. Further granularity revealed substantial gains in energy efficiency and cost reduction across different scheduling intensities: 11.11% in light schedules, 20.09% in medium schedules, and an impressive 38.85% in heavy schedules. However, this research does not shy away from highlighting challenges related to data quality, computational demands, and generalizability. Future research trajectories encompass the development of adaptive models tailored to diverse data qualities, enhancements in scalability for and adaptability to various microgrid configurations, the integration of real-time data, the accommodation of user preferences, the exploration of energy storage and renewables, and an imperative focus on enhancing algorithm transparency.
{"title":"A Scheduling Algorithm for Appliance Energy Consumption Optimization in a Dynamic Pricing Environment","authors":"Hamza Touhs, Anas Temouden, A. Khallaayoun, Mhammed Chraibi, Hamza El Hafdaoui","doi":"10.3390/wevj15010001","DOIUrl":"https://doi.org/10.3390/wevj15010001","url":null,"abstract":"This research delves into the intricate landscape of energy scheduling and optimization within microgrid and residential contexts, addressing pivotal aspects such as real-time scheduling systems, challenges in dynamic pricing, and an array of optimization strategies. This paper introduces a cutting-edge scheduling algorithm, harnessing the power of artificial neural networks driven by Long Short-Term Memory Networks, and highlights its exceptional performance, boasting a significantly lower Mean Absolute Error of 5.32 compared to conventional models. This heightened predictive accuracy translates into tangible improvements in both energy efficiency and cost savings. This study underscores the delicate balance between user satisfaction, cost reduction, and efficient scheduling for sustainable energy consumption, showcasing a remarkable 38% enhancement in optimized schedules. Further granularity revealed substantial gains in energy efficiency and cost reduction across different scheduling intensities: 11.11% in light schedules, 20.09% in medium schedules, and an impressive 38.85% in heavy schedules. However, this research does not shy away from highlighting challenges related to data quality, computational demands, and generalizability. Future research trajectories encompass the development of adaptive models tailored to diverse data qualities, enhancements in scalability for and adaptability to various microgrid configurations, the integration of real-time data, the accommodation of user preferences, the exploration of energy storage and renewables, and an imperative focus on enhancing algorithm transparency.","PeriodicalId":38979,"journal":{"name":"World Electric Vehicle Journal","volume":" 7","pages":""},"PeriodicalIF":2.3,"publicationDate":"2023-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138963099","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}
Daniel Mortensen, Jacob Gunther, Greg Droge, Justin Whitaker
Recent attention for reduced carbon emissions has pushed transit authorities to adopt battery electric buses (BEBs). One challenge experienced by BEB users is extended charge times, which create logistical challenges and may force BEBs to charge when energy is more expensive. Furthermore, BEB charging leads to high power demands, which can significantly increase monthly power costs and may push the electrical infrastructure beyond its present capacity, requiring expensive upgrades. This work presents a novel method for minimizing the monthly cost of BEB charging while meeting bus route constraints. This method extends previous work by incorporating a more novel cost model, effects from uncontrolled loads, differences between daytime and overnight charging, and variable rate charging. A graph-based network-flow framework, represented by a mixed-integer linear program, encodes the charging action space, physical bus constraints, and battery state of the charge dynamics. The results for three scenarios are considered: uncontested charging, which uses equal numbers of buses and chargers; contested charging, which has more buses than chargers; and variable charge rates. Among other findings, we show that BEBs can be added to the fleet without raising the peak power demand for only the cost of the energy, suggesting that conversion to electrified transit is possible without upgrading power delivery infrastructure.
{"title":"Cost Minimization for Charging Electric Bus Fleets","authors":"Daniel Mortensen, Jacob Gunther, Greg Droge, Justin Whitaker","doi":"10.3390/wevj14120351","DOIUrl":"https://doi.org/10.3390/wevj14120351","url":null,"abstract":"Recent attention for reduced carbon emissions has pushed transit authorities to adopt battery electric buses (BEBs). One challenge experienced by BEB users is extended charge times, which create logistical challenges and may force BEBs to charge when energy is more expensive. Furthermore, BEB charging leads to high power demands, which can significantly increase monthly power costs and may push the electrical infrastructure beyond its present capacity, requiring expensive upgrades. This work presents a novel method for minimizing the monthly cost of BEB charging while meeting bus route constraints. This method extends previous work by incorporating a more novel cost model, effects from uncontrolled loads, differences between daytime and overnight charging, and variable rate charging. A graph-based network-flow framework, represented by a mixed-integer linear program, encodes the charging action space, physical bus constraints, and battery state of the charge dynamics. The results for three scenarios are considered: uncontested charging, which uses equal numbers of buses and chargers; contested charging, which has more buses than chargers; and variable charge rates. Among other findings, we show that BEBs can be added to the fleet without raising the peak power demand for only the cost of the energy, suggesting that conversion to electrified transit is possible without upgrading power delivery infrastructure.","PeriodicalId":38979,"journal":{"name":"World Electric Vehicle Journal","volume":"55 37","pages":""},"PeriodicalIF":2.3,"publicationDate":"2023-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138995636","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}
Thomas Cawkwell, Ahmed Haris, Juan Manuel Gonzalez, Leon Kevin Rodrigues, Vladimir Shirokov
Interior permanent magnet (IPM) motors in traction applications often employ discrete rotor skewing constructions to reduce torsional excitations and back-EMF harmonics. Although skewing is very effective in reducing cogging torque, the impact on torque ripple is not well understood and can vary significantly over the operating envelope of a motor. Skewing also leads to the creation of a non-zero axial force that may compromise the bearing life if not considered. This paper introduces a holistic methodology for analyzing the effect of skewing, aiming to minimize torsional excitations, axial forces and back-EMF harmonics whilst mitigating the impact on performance and costs. Firstly, analytical models are employed for calculating cogging torque, torque ripple and axial forces. Then, 2D and 3D finite element analysis are used to incorporate the influence of non-linear material behavior. A detailed structural model of the powertrain is employed to calculate the radiated noise and identify key areas allowing a motor designer to reduce noise, vibration and harshness (NVH). A meticulous selection process for the skewing angle, the number of skew stacks and the orientation of skew stacks is developed, giving particular attention to the effect of the selected pattern on NVH in both forward and reverse rotating directions.
{"title":"A Methodology for Applying Skew in an Automotive Interior Permanent Magnet Rotor for Robust Electromagnetic and Noise, Vibration and Harshness Performance","authors":"Thomas Cawkwell, Ahmed Haris, Juan Manuel Gonzalez, Leon Kevin Rodrigues, Vladimir Shirokov","doi":"10.3390/wevj14120350","DOIUrl":"https://doi.org/10.3390/wevj14120350","url":null,"abstract":"Interior permanent magnet (IPM) motors in traction applications often employ discrete rotor skewing constructions to reduce torsional excitations and back-EMF harmonics. Although skewing is very effective in reducing cogging torque, the impact on torque ripple is not well understood and can vary significantly over the operating envelope of a motor. Skewing also leads to the creation of a non-zero axial force that may compromise the bearing life if not considered. This paper introduces a holistic methodology for analyzing the effect of skewing, aiming to minimize torsional excitations, axial forces and back-EMF harmonics whilst mitigating the impact on performance and costs. Firstly, analytical models are employed for calculating cogging torque, torque ripple and axial forces. Then, 2D and 3D finite element analysis are used to incorporate the influence of non-linear material behavior. A detailed structural model of the powertrain is employed to calculate the radiated noise and identify key areas allowing a motor designer to reduce noise, vibration and harshness (NVH). A meticulous selection process for the skewing angle, the number of skew stacks and the orientation of skew stacks is developed, giving particular attention to the effect of the selected pattern on NVH in both forward and reverse rotating directions.","PeriodicalId":38979,"journal":{"name":"World Electric Vehicle Journal","volume":"24 62","pages":""},"PeriodicalIF":2.3,"publicationDate":"2023-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139000772","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}
There has been significant EV sales growth in Europe, benefiting from its policies for promoting electric vehicles (EVs) and investments in manufacturing. This study investigates the investment announcements for EV and battery production announced by manufacturers and compares them to four scenarios with different EV penetration levels in Europe. This study projects the required capacities and estimates the investment needs to meet different EV sale targets in each scenario. The investigations show that, for Europe to achieve 60% new EV sales by 2030 and to be on track for 100% by 2035, its 4.8 million planned production capacity of EVs would fall short of the needed 9.2 million in 2030. The gap could close to 2.0 million when tentative announcements are counted. The results for batteries indicate that tentative plans are adequate and firm plans can satisfy most scenarios by 2030. More investments into EV production, along with policy support and incentives, are needed for more rapid scenarios.
{"title":"Investigating Investment Plans for Expanding Battery and Electric Vehicle Production in Europe","authors":"Hong Yang, Lewis Fulton","doi":"10.3390/wevj14120347","DOIUrl":"https://doi.org/10.3390/wevj14120347","url":null,"abstract":"There has been significant EV sales growth in Europe, benefiting from its policies for promoting electric vehicles (EVs) and investments in manufacturing. This study investigates the investment announcements for EV and battery production announced by manufacturers and compares them to four scenarios with different EV penetration levels in Europe. This study projects the required capacities and estimates the investment needs to meet different EV sale targets in each scenario. The investigations show that, for Europe to achieve 60% new EV sales by 2030 and to be on track for 100% by 2035, its 4.8 million planned production capacity of EVs would fall short of the needed 9.2 million in 2030. The gap could close to 2.0 million when tentative announcements are counted. The results for batteries indicate that tentative plans are adequate and firm plans can satisfy most scenarios by 2030. More investments into EV production, along with policy support and incentives, are needed for more rapid scenarios.","PeriodicalId":38979,"journal":{"name":"World Electric Vehicle Journal","volume":"22 14","pages":""},"PeriodicalIF":2.3,"publicationDate":"2023-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138972237","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}
Vennapusa Jagadeeswara Reddy, N. P. Hariram, Rittick Maity, Mohd Fairusham Ghazali, Sudhakar Kumarasamy
Increasingly stringent sustainability and decarbonization objectives drive investments in adopting environmentally friendly, low, and zero-carbon fuels. This study presents a comparative framework of green hydrogen, green ammonia, and green methanol production and application in a clear context. By harnessing publicly available data sources, including from the literature, this research delves into the evaluation of green fuels. Building on these insights, this study outlines the production process, application, and strategic pathways to transition into a greener economy by 2050. This envisioned transformation unfolds in three progressive steps: the utilization of green hydrogen, green ammonia, and green methanol as a sustainable fuel source for transport applications; the integration of these green fuels in industries; and the establishment of mechanisms for achieving the net zero. However, this research also reveals the formidable challenges of producing green hydrogen, green ammonia, and green methanol. These challenges encompass technological intricacies, economic barriers, societal considerations, and far-reaching policy implications necessitating collaborative efforts and innovative solutions to successfully develop and deploy green hydrogen, green ammonia, and green methanol. The findings unequivocally demonstrate that renewable energy sources play a pivotal role in enabling the production of these green fuels, positioning the global transition in the landscape of sustainable energy.
{"title":"Sustainable E-Fuels: Green Hydrogen, Methanol and Ammonia for Carbon-Neutral Transportation","authors":"Vennapusa Jagadeeswara Reddy, N. P. Hariram, Rittick Maity, Mohd Fairusham Ghazali, Sudhakar Kumarasamy","doi":"10.3390/wevj14120349","DOIUrl":"https://doi.org/10.3390/wevj14120349","url":null,"abstract":"Increasingly stringent sustainability and decarbonization objectives drive investments in adopting environmentally friendly, low, and zero-carbon fuels. This study presents a comparative framework of green hydrogen, green ammonia, and green methanol production and application in a clear context. By harnessing publicly available data sources, including from the literature, this research delves into the evaluation of green fuels. Building on these insights, this study outlines the production process, application, and strategic pathways to transition into a greener economy by 2050. This envisioned transformation unfolds in three progressive steps: the utilization of green hydrogen, green ammonia, and green methanol as a sustainable fuel source for transport applications; the integration of these green fuels in industries; and the establishment of mechanisms for achieving the net zero. However, this research also reveals the formidable challenges of producing green hydrogen, green ammonia, and green methanol. These challenges encompass technological intricacies, economic barriers, societal considerations, and far-reaching policy implications necessitating collaborative efforts and innovative solutions to successfully develop and deploy green hydrogen, green ammonia, and green methanol. The findings unequivocally demonstrate that renewable energy sources play a pivotal role in enabling the production of these green fuels, positioning the global transition in the landscape of sustainable energy.","PeriodicalId":38979,"journal":{"name":"World Electric Vehicle Journal","volume":"1 2","pages":""},"PeriodicalIF":2.3,"publicationDate":"2023-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138971978","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}
With the rapid breakthroughs in artificial intelligence technology and intelligent manufacturing technology, automotive intelligence has become a research hotspot, and much progress has been made. However, a skeptical attitude is still held towards intelligent vehicles, especially when driving in a complex multi-vehicle interaction environment. The interaction among multi-vehicles generally involves more uncertainties in vehicle motion and entails higher driving risk, and thus deserves more research concerns and efforts. Targeting the safety assessment issue of complex multi-vehicle interaction scenarios, this article summarizes the existing literature on the relevant data collection methodologies, vehicle interaction mechanisms, and driving risk evaluation methods for intelligent vehicles. The limitations of the existing assessment methods and the prospects for their future development are analyzed. The results of this article can provide a reference for intelligent vehicles in terms of timely and accurate driving risk assessment in real-world multi-vehicle scenarios and help improve the safe driving technologies of intelligent vehicles.
{"title":"Review of Intelligent Vehicle Driving Risk Assessment in Multi-Vehicle Interaction Scenarios","authors":"Xiaoxia Xiong, Shiya Zhang, Yuexia Chen","doi":"10.3390/wevj14120348","DOIUrl":"https://doi.org/10.3390/wevj14120348","url":null,"abstract":"With the rapid breakthroughs in artificial intelligence technology and intelligent manufacturing technology, automotive intelligence has become a research hotspot, and much progress has been made. However, a skeptical attitude is still held towards intelligent vehicles, especially when driving in a complex multi-vehicle interaction environment. The interaction among multi-vehicles generally involves more uncertainties in vehicle motion and entails higher driving risk, and thus deserves more research concerns and efforts. Targeting the safety assessment issue of complex multi-vehicle interaction scenarios, this article summarizes the existing literature on the relevant data collection methodologies, vehicle interaction mechanisms, and driving risk evaluation methods for intelligent vehicles. The limitations of the existing assessment methods and the prospects for their future development are analyzed. The results of this article can provide a reference for intelligent vehicles in terms of timely and accurate driving risk assessment in real-world multi-vehicle scenarios and help improve the safe driving technologies of intelligent vehicles.","PeriodicalId":38979,"journal":{"name":"World Electric Vehicle Journal","volume":"28 3","pages":""},"PeriodicalIF":2.3,"publicationDate":"2023-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138971703","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. Aldakkhelallah, Abdulrahman S. Alamri, Stelios Georgiou, Milan Simic
Autonomous vehicles (AVs) will transform transport, but public opinion will play a key role in decisions on how widely and quickly they are adopted. The purpose of the study presented here was to investigate community’s views on that transition. As a method for primary data collection on public awareness, attitudes, and readiness to use autonomous cars, survey was conducted in Saudi Arabia. Following that, we used statistical tools to analyse responses. Our findings indicate that the participants are largely receptive to using new technologies and had favourable attitudes towards the transition. Ordinal logistic regression model showed a wide variation in public opinion regarding the expected benefits that may accompany the transition. Our findings reveal that awareness of AVs’ benefits is positively correlated with the age of participants. Perceived costs on one side, and convenience and safety on the other, were found to have had a substantial impact on the opinions of the participants. Investigation presented here shows a sample of the public’s perception of AVs in Saudi Arabia. This can guide the development of AVs and their deployment in that region as well as worldwide.
{"title":"Public Perception of the Introduction of Autonomous Vehicles","authors":"A. Aldakkhelallah, Abdulrahman S. Alamri, Stelios Georgiou, Milan Simic","doi":"10.3390/wevj14120345","DOIUrl":"https://doi.org/10.3390/wevj14120345","url":null,"abstract":"Autonomous vehicles (AVs) will transform transport, but public opinion will play a key role in decisions on how widely and quickly they are adopted. The purpose of the study presented here was to investigate community’s views on that transition. As a method for primary data collection on public awareness, attitudes, and readiness to use autonomous cars, survey was conducted in Saudi Arabia. Following that, we used statistical tools to analyse responses. Our findings indicate that the participants are largely receptive to using new technologies and had favourable attitudes towards the transition. Ordinal logistic regression model showed a wide variation in public opinion regarding the expected benefits that may accompany the transition. Our findings reveal that awareness of AVs’ benefits is positively correlated with the age of participants. Perceived costs on one side, and convenience and safety on the other, were found to have had a substantial impact on the opinions of the participants. Investigation presented here shows a sample of the public’s perception of AVs in Saudi Arabia. This can guide the development of AVs and their deployment in that region as well as worldwide.","PeriodicalId":38979,"journal":{"name":"World Electric Vehicle Journal","volume":"3 2","pages":""},"PeriodicalIF":2.3,"publicationDate":"2023-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139007096","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}
Aiming at the instability problem of a four-wheel independent drive electric bus under high-speed conditions, this paper first designs a vehicle yaw stability controller based on a linear two-degree-of-freedom model and a linear quadratic programming (LQR) algorithm. A vehicle roll stability controller is then designed based on a linear three-degree-of-freedom model and a model predictive control algorithm (MPC). Moreover, a coordinated control rule based on the lateral load transfer rate (LTR) is designed for the coupled problem of yaw and roll dynamics. Finally, the effectiveness of the proposed control algorithm is verified by simulation. The obtained results show that when the vehicle is running at a high speed of 90 km/h, the stability control algorithm can control the yaw rate tracking error within 0.05 rad/s. In addition, the control algorithm can reduce the maximum amplitude of the side slip angle, the maximum value of the roll angle, the maximum value of the roll angular velocity, and the amplitude of the lateral acceleration by more than 96%, 81.1%, 65.0%, and 11.1%, respectively.
针对四轮独立驱动电动客车在高速条件下的不稳定性问题，本文首先基于线性二自由度模型和线性二次编程（LQR）算法设计了车辆偏航稳定性控制器。然后，基于线性三自由度模型和模型预测控制算法（MPC）设计了车辆侧倾稳定性控制器。此外，还针对偏航和侧倾动态耦合问题设计了基于横向负载转移率（LTR）的协调控制规则。最后，通过仿真验证了所提控制算法的有效性。结果表明，当车辆以 90 km/h 的高速行驶时，稳定控制算法可将偏航率跟踪误差控制在 0.05 rad/s 以内。此外，该控制算法还能将侧滑角最大振幅、侧滚角最大值、侧滚角速度最大值和侧向加速度振幅分别降低 96%、81.1%、65.0% 和 11.1%以上。
{"title":"Research on Stability Control Algorithm of Distributed Drive Bus under High-Speed Conditions","authors":"Shaopeng Zhu, Bangxuan Wei, Chen Ping, Minjun Shi, Chen Wang, Hui-yan Chen, Minglu Han","doi":"10.3390/wevj14120343","DOIUrl":"https://doi.org/10.3390/wevj14120343","url":null,"abstract":"Aiming at the instability problem of a four-wheel independent drive electric bus under high-speed conditions, this paper first designs a vehicle yaw stability controller based on a linear two-degree-of-freedom model and a linear quadratic programming (LQR) algorithm. A vehicle roll stability controller is then designed based on a linear three-degree-of-freedom model and a model predictive control algorithm (MPC). Moreover, a coordinated control rule based on the lateral load transfer rate (LTR) is designed for the coupled problem of yaw and roll dynamics. Finally, the effectiveness of the proposed control algorithm is verified by simulation. The obtained results show that when the vehicle is running at a high speed of 90 km/h, the stability control algorithm can control the yaw rate tracking error within 0.05 rad/s. In addition, the control algorithm can reduce the maximum amplitude of the side slip angle, the maximum value of the roll angle, the maximum value of the roll angular velocity, and the amplitude of the lateral acceleration by more than 96%, 81.1%, 65.0%, and 11.1%, respectively.","PeriodicalId":38979,"journal":{"name":"World Electric Vehicle Journal","volume":"20 3","pages":""},"PeriodicalIF":2.3,"publicationDate":"2023-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139009201","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}
This paper presents a comprehensive study on autonomous vehicle parking challenges, focusing on kinematic and reverse parking models. The research develops models for various scenarios, including turning, reverse, vertical, and parallel parking while using the minimum turning radius solution. The integration of the A* algorithm enhances trajectory optimization and obstacle avoidance. Innovative concepts like NTBPT and B-spline theory improve computational optimization. This study provides a foundation for understanding the dynamics and constraints of autonomous parking. The proposed model enhances efficiency and safety, reducing algorithm complexity and improving trajectory optimization. This research offers valuable insights and methodologies for addressing autonomous vehicle parking challenges and advocates for advancements in automated parking systems.
{"title":"Optimization Design of Parking Models Based on Complex and Random Parking Environments","authors":"Xunchen Liu, Siqi Zhu, Yuan Fang, Yutong Wang, Lijuan Fu, Wenjing Lei, Zijian Zhou","doi":"10.3390/wevj14120344","DOIUrl":"https://doi.org/10.3390/wevj14120344","url":null,"abstract":"This paper presents a comprehensive study on autonomous vehicle parking challenges, focusing on kinematic and reverse parking models. The research develops models for various scenarios, including turning, reverse, vertical, and parallel parking while using the minimum turning radius solution. The integration of the A* algorithm enhances trajectory optimization and obstacle avoidance. Innovative concepts like NTBPT and B-spline theory improve computational optimization. This study provides a foundation for understanding the dynamics and constraints of autonomous parking. The proposed model enhances efficiency and safety, reducing algorithm complexity and improving trajectory optimization. This research offers valuable insights and methodologies for addressing autonomous vehicle parking challenges and advocates for advancements in automated parking systems.","PeriodicalId":38979,"journal":{"name":"World Electric Vehicle Journal","volume":"34 9","pages":""},"PeriodicalIF":2.3,"publicationDate":"2023-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139008971","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}
As the upgrade of people’s requirements for automotive driving comfort, conventional passive suspensions for cars have fallen short of existing demands due to their nonadjustable damping and stiffness, so semiactive suspensions and active suspensions have gained growing acceptance. Compared with active suspensions, semiactive suspensions offer the advantages of a low manufacturing cost and reliable structure, and thus have become the preferred choice for most vehicles. To optimize the control effect of semiactive suspensions under different working conditions, this paper completed the modeling of magnetorheological semiactive suspension system dynamics and road inputs; then, the design of binocular camera sensing algorithms was performed to obtain the real-time distance of the target using the point cloud ranging function, and the parameters required for suspension control were also obtained. This was followed by the completion of the control-mode-switching rules and the design of the suspension controller. According to the different control objectives, the mode could be divided into the obstacle-road mode, straight-road mode, and curved-road mode. The suspension controller included the BP-PID (neural network PID controller) controller and the force distributor. Finally, the effectiveness of the mode-switching rules and the control method was verified through system simulation and the hardware-in-the-loop test.
{"title":"Research on the Multimode Switching Control of Intelligent Suspension Based on Binocular Distance Recognition","authors":"Chen Huang, Kunyan Lv, Qing Xu, Yifan Dai","doi":"10.3390/wevj14120340","DOIUrl":"https://doi.org/10.3390/wevj14120340","url":null,"abstract":"As the upgrade of people’s requirements for automotive driving comfort, conventional passive suspensions for cars have fallen short of existing demands due to their nonadjustable damping and stiffness, so semiactive suspensions and active suspensions have gained growing acceptance. Compared with active suspensions, semiactive suspensions offer the advantages of a low manufacturing cost and reliable structure, and thus have become the preferred choice for most vehicles. To optimize the control effect of semiactive suspensions under different working conditions, this paper completed the modeling of magnetorheological semiactive suspension system dynamics and road inputs; then, the design of binocular camera sensing algorithms was performed to obtain the real-time distance of the target using the point cloud ranging function, and the parameters required for suspension control were also obtained. This was followed by the completion of the control-mode-switching rules and the design of the suspension controller. According to the different control objectives, the mode could be divided into the obstacle-road mode, straight-road mode, and curved-road mode. The suspension controller included the BP-PID (neural network PID controller) controller and the force distributor. Finally, the effectiveness of the mode-switching rules and the control method was verified through system simulation and the hardware-in-the-loop test.","PeriodicalId":38979,"journal":{"name":"World Electric Vehicle Journal","volume":"54 23","pages":""},"PeriodicalIF":2.3,"publicationDate":"2023-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138593050","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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