In this work,we present a photovoltaic(PV)-based off-board charging system integrated with the grid using a voltage source converter(VSC).The control of the grid-tied off-board charger is derived from the joint logari...In this work,we present a photovoltaic(PV)-based off-board charging system integrated with the grid using a voltage source converter(VSC).The control of the grid-tied off-board charger is derived from the joint logarithmic hyperbolic cosine robust sparse adaptive filter(JLHCAF)algorithm.This algorithm effectively tracks the fundamental component of the load current in a short duration,providing a good dynamic response.Due to its robustness against impulsive interference,the JLHCAF outperforms other sparsity-aware robust algorithms The cascaded proportional-integral(PI)controller is used to control the bidirectional buck-boost converter for electric vehicle(EV)charging/discharging,which acts in buck operation if the EV is being charged and in boost operation if it is discharged.The reference DC link voltage for the controller is derived by using adaptive MPPT technique.The bidirectional properties of the system enable various functions,including grid-to-vehicle(G2V),vehicle-to-grid(V2G),PV source-to-grid(PV2G),vehicle-to-home(V2H),and PV source-to-vehicle(PV2V)operations.Additionally,the system can supply power to critical nonlinear loads.The control strategy ensures compliance with the power quality requirements set by the IEEE standard,as demonstrated in the results.To validate the effectiveness of the proposed system,we conducted tests under dynamic conditions by disconnecting and reconnecting household loads.Furthermore,the off-board charging system was subjected to actual conditions,such as variations in solar PV insolation,and its steady-state performance was evaluated through simulation and laboratory experimental prototypes.The results,including total harmonic distortion(THD),support the validation of the developed charging system.展开更多
Many surveys on vehicle traffic safety have shown that the tire road friction coefficient(TRFC)is correlated with the probability of an accident.The probability of road accidents increases sharply on slippery road sur...Many surveys on vehicle traffic safety have shown that the tire road friction coefficient(TRFC)is correlated with the probability of an accident.The probability of road accidents increases sharply on slippery road surfaces.Therefore,accurate knowledge of TRFC contributes to the optimization of driver maneuvers for further improving the safety of intelligent vehicles.A large number of researchers have employed different tools and proposed different algorithms to obtain TRFC.This work investigates these different methods that have been widely utilized to estimate TRFC.These methods are divided into three main categories:off-board sensors-based,vehicle dynamics-based,and data-driven-based methods.This review provides a comparative analysis of these methods and describes their strengths and weaknesses.Moreover,some future research directions regarding TRFC estimation are presented.展开更多
基金Supported by the MPCST and SERB,India,for supporting through start-up research grant(SRG/2020/001742).
文摘In this work,we present a photovoltaic(PV)-based off-board charging system integrated with the grid using a voltage source converter(VSC).The control of the grid-tied off-board charger is derived from the joint logarithmic hyperbolic cosine robust sparse adaptive filter(JLHCAF)algorithm.This algorithm effectively tracks the fundamental component of the load current in a short duration,providing a good dynamic response.Due to its robustness against impulsive interference,the JLHCAF outperforms other sparsity-aware robust algorithms The cascaded proportional-integral(PI)controller is used to control the bidirectional buck-boost converter for electric vehicle(EV)charging/discharging,which acts in buck operation if the EV is being charged and in boost operation if it is discharged.The reference DC link voltage for the controller is derived by using adaptive MPPT technique.The bidirectional properties of the system enable various functions,including grid-to-vehicle(G2V),vehicle-to-grid(V2G),PV source-to-grid(PV2G),vehicle-to-home(V2H),and PV source-to-vehicle(PV2V)operations.Additionally,the system can supply power to critical nonlinear loads.The control strategy ensures compliance with the power quality requirements set by the IEEE standard,as demonstrated in the results.To validate the effectiveness of the proposed system,we conducted tests under dynamic conditions by disconnecting and reconnecting household loads.Furthermore,the off-board charging system was subjected to actual conditions,such as variations in solar PV insolation,and its steady-state performance was evaluated through simulation and laboratory experimental prototypes.The results,including total harmonic distortion(THD),support the validation of the developed charging system.
基金Supported by the National Natural Science Funds for Distinguished Young Scholar of China(Grant No.52025121)National Natural Science Foundation of China(Grant Nos.51975118,52002066).
文摘Many surveys on vehicle traffic safety have shown that the tire road friction coefficient(TRFC)is correlated with the probability of an accident.The probability of road accidents increases sharply on slippery road surfaces.Therefore,accurate knowledge of TRFC contributes to the optimization of driver maneuvers for further improving the safety of intelligent vehicles.A large number of researchers have employed different tools and proposed different algorithms to obtain TRFC.This work investigates these different methods that have been widely utilized to estimate TRFC.These methods are divided into three main categories:off-board sensors-based,vehicle dynamics-based,and data-driven-based methods.This review provides a comparative analysis of these methods and describes their strengths and weaknesses.Moreover,some future research directions regarding TRFC estimation are presented.
