Vector control schemes have recently been used to drive linear induction motors(LIM)in high-performance applications.This trend promotes the development of precise and efficient control schemes for individual motors.T...Vector control schemes have recently been used to drive linear induction motors(LIM)in high-performance applications.This trend promotes the development of precise and efficient control schemes for individual motors.This research aims to present a novel framework for speed and thrust force control of LIM using space vector pulse width modulation(SVPWM)inverters.The framework under consideration is developed in four stages.To begin,MATLAB Simulink was used to develop a detailed mathematical and electromechanical dynamicmodel.The research presents a modified SVPWM inverter control scheme.By tuning the proportional-integral(PI)controller with a transfer function,optimized values for the PI controller are derived.All the subsystems mentioned above are integrated to create a robust simulation of the LIM’s precise speed and thrust force control scheme.The reference speed values were chosen to evaluate the performance of the respective system,and the developed system’s response was verified using various data sets.For the low-speed range,a reference value of 10m/s is used,while a reference value of 100 m/s is used for the high-speed range.The speed output response indicates that themotor reached reference speed in amatter of seconds,as the delay time is between 8 and 10 s.The maximum amplitude of thrust achieved is less than 400N,demonstrating the controller’s capability to control a high-speed LIM with minimal thrust ripple.Due to the controlled speed range,the developed system is highly recommended for low-speed and high-speed and heavy-duty traction applications.展开更多
As the adoption of Electric Vehicles(EVs)intensifies,two primary challenges emerge:limited range due to battery constraints and extended charging times.The traditional charging stations,particularly those near highway...As the adoption of Electric Vehicles(EVs)intensifies,two primary challenges emerge:limited range due to battery constraints and extended charging times.The traditional charging stations,particularly those near highways,exacerbate these issues with necessary detours,inconsistent service levels,and unpredictable waiting durations.The emerging technology of dynamic wireless charging lanes(DWCLs)may alleviate range anxiety and eliminate long charging stops;however,the driving speed on DWCL significantly affects charging efficiency and effective charging time.Meanwhile,the existing research has addressed load balancing optimization on Dynamic Wireless Charging(DWC)systems to a limited extent.To address this critical issue,this study introduces an innovative eco-driving speed control strategy,providing a novel solution to the multi-objective optimization problem of speed control on DWCL.We utilize mathematical programming methods and incorporate the longitudinal dynamics of vehicles to provide an accurate physical model of EVs.Three objective functions are formulated to tackle the challenges at hand:reducing travel time,increasing charging efficiency,and achieving load balancing on DWCL,which corresponds to four control strategies.The results of numerical tests indicate that a comprehensive control strategy,which considers all objectives,achieves a minor sacrifice in travel time reduction while significantly improving energy efficiency and load balancing.Furthermore,by defining the energy demand and speed range through an upper operation limit,a relatively superior speed control strategy can be selected.This work contributes to the discourse on DWCL integration into modern transportation systems,enhancing the EV driving experience on major roads.展开更多
基金The authors extend their appreciation to the Deanship of Scientific Research at King Khalid University for funding this work through Large Groups Project under grant number(RGP.2/111/43).
文摘Vector control schemes have recently been used to drive linear induction motors(LIM)in high-performance applications.This trend promotes the development of precise and efficient control schemes for individual motors.This research aims to present a novel framework for speed and thrust force control of LIM using space vector pulse width modulation(SVPWM)inverters.The framework under consideration is developed in four stages.To begin,MATLAB Simulink was used to develop a detailed mathematical and electromechanical dynamicmodel.The research presents a modified SVPWM inverter control scheme.By tuning the proportional-integral(PI)controller with a transfer function,optimized values for the PI controller are derived.All the subsystems mentioned above are integrated to create a robust simulation of the LIM’s precise speed and thrust force control scheme.The reference speed values were chosen to evaluate the performance of the respective system,and the developed system’s response was verified using various data sets.For the low-speed range,a reference value of 10m/s is used,while a reference value of 100 m/s is used for the high-speed range.The speed output response indicates that themotor reached reference speed in amatter of seconds,as the delay time is between 8 and 10 s.The maximum amplitude of thrust achieved is less than 400N,demonstrating the controller’s capability to control a high-speed LIM with minimal thrust ripple.Due to the controlled speed range,the developed system is highly recommended for low-speed and high-speed and heavy-duty traction applications.
基金funded by the National Natural Science Foundation of China(72201149)Xinjiang Key Laboratory of Green Mining of Coal resources,Ministry of Education(KLXGY-KB2420)Guangzhou Basic and Applied Basic Research(SL2023A04J00802).
文摘As the adoption of Electric Vehicles(EVs)intensifies,two primary challenges emerge:limited range due to battery constraints and extended charging times.The traditional charging stations,particularly those near highways,exacerbate these issues with necessary detours,inconsistent service levels,and unpredictable waiting durations.The emerging technology of dynamic wireless charging lanes(DWCLs)may alleviate range anxiety and eliminate long charging stops;however,the driving speed on DWCL significantly affects charging efficiency and effective charging time.Meanwhile,the existing research has addressed load balancing optimization on Dynamic Wireless Charging(DWC)systems to a limited extent.To address this critical issue,this study introduces an innovative eco-driving speed control strategy,providing a novel solution to the multi-objective optimization problem of speed control on DWCL.We utilize mathematical programming methods and incorporate the longitudinal dynamics of vehicles to provide an accurate physical model of EVs.Three objective functions are formulated to tackle the challenges at hand:reducing travel time,increasing charging efficiency,and achieving load balancing on DWCL,which corresponds to four control strategies.The results of numerical tests indicate that a comprehensive control strategy,which considers all objectives,achieves a minor sacrifice in travel time reduction while significantly improving energy efficiency and load balancing.Furthermore,by defining the energy demand and speed range through an upper operation limit,a relatively superior speed control strategy can be selected.This work contributes to the discourse on DWCL integration into modern transportation systems,enhancing the EV driving experience on major roads.
