A robust sliding mode approach combined with a field oriented control （FOC） for induction motor （IM） speed control is presented. The proposed sliding mode control （SMC） design uses an adaptive switching gain and...A robust sliding mode approach combined with a field oriented control （FOC） for induction motor （IM） speed control is presented. The proposed sliding mode control （SMC） design uses an adaptive switching gain and an integrator. This approach guarantees the same robustness and dynamic performance of traditional SMC algorithms. And at the same time, it attenuates the chattering phenomenon, which is the main drawback in actual implementation of this technique. This approach is insensitive to uncertainties and permits to decrease the requirement for the bound of these uncertainties. The stability and robustness of the closed- loop system are proven analytically using the Lyapunov synthesis approach. The proposed method attenuates the effect of both uncertainties and external disturbances. Experimental results are presented to validate the effectiveness and the good performance of the developed method.展开更多
本文设计了一种适用于电机矢量控制算法的数字信号处理系统的微架构定义,包括其指令集定义、存储器模型以及与主CPU的交互模式.该设计具有通过固定部分多操作数有效缩减指令编码长度提高代码密度以及后台执行多周期指令提高ALU并行效率...本文设计了一种适用于电机矢量控制算法的数字信号处理系统的微架构定义,包括其指令集定义、存储器模型以及与主CPU的交互模式.该设计具有通过固定部分多操作数有效缩减指令编码长度提高代码密度以及后台执行多周期指令提高ALU并行效率的显著优点.文中给出了典型的FOC控制算法在DSP(Digital Signal Processor)指令集上实现的指令周期数,也给出了对应架构的电路实现情况,最终以ARM CORTEX-M0及几款主流DSP作为比较基线,通过实测实验数据证明了体系结构的高能效比,以较为有限的电路面积代价,极大提高了集成DSP的嵌入式系统的运行效率.展开更多
The existing research of the acceleration control mainly focuses on an optimization of the velocity trajectory with respect to a criterion formulation that weights acceleration time and fuel consumption.The minimum-fu...The existing research of the acceleration control mainly focuses on an optimization of the velocity trajectory with respect to a criterion formulation that weights acceleration time and fuel consumption.The minimum-fuel acceleration problem in conventional vehicle has been solved by Pontryagin's maximum principle and dynamic programming algorithm,respectively.The acceleration control with minimum energy consumption for battery electric vehicle(EV)has not been reported.In this paper,the permanent magnet synchronous motor(PMSM)is controlled by the field oriented control(FOC)method and the electric drive system for the EV(including the PMSM,the inverter and the battery)is modeled to favor over a detailed consumption map.The analytical algorithm is proposed to analyze the optimal acceleration control and the optimal torque versus speed curve in the acceleration process is obtained.Considering the acceleration time,a penalty function is introduced to realize a fast vehicle speed tracking.The optimal acceleration control is also addressed with dynamic programming(DP).This method can solve the optimal acceleration problem with precise time constraint,but it consumes a large amount of computation time.The EV used in simulation and experiment is a four-wheel hub motor drive electric vehicle.The simulation and experimental results show that the required battery energy has little difference between the acceleration control solved by analytical algorithm and that solved by DP,and is greatly reduced comparing with the constant pedal opening acceleration.The proposed analytical and DP algorithms can minimize the energy consumption in EV's acceleration process and the analytical algorithm is easy to be implemented in real-time control.展开更多
文摘A robust sliding mode approach combined with a field oriented control （FOC） for induction motor （IM） speed control is presented. The proposed sliding mode control （SMC） design uses an adaptive switching gain and an integrator. This approach guarantees the same robustness and dynamic performance of traditional SMC algorithms. And at the same time, it attenuates the chattering phenomenon, which is the main drawback in actual implementation of this technique. This approach is insensitive to uncertainties and permits to decrease the requirement for the bound of these uncertainties. The stability and robustness of the closed- loop system are proven analytically using the Lyapunov synthesis approach. The proposed method attenuates the effect of both uncertainties and external disturbances. Experimental results are presented to validate the effectiveness and the good performance of the developed method.
文摘本文设计了一种适用于电机矢量控制算法的数字信号处理系统的微架构定义,包括其指令集定义、存储器模型以及与主CPU的交互模式.该设计具有通过固定部分多操作数有效缩减指令编码长度提高代码密度以及后台执行多周期指令提高ALU并行效率的显著优点.文中给出了典型的FOC控制算法在DSP(Digital Signal Processor)指令集上实现的指令周期数,也给出了对应架构的电路实现情况,最终以ARM CORTEX-M0及几款主流DSP作为比较基线,通过实测实验数据证明了体系结构的高能效比,以较为有限的电路面积代价,极大提高了集成DSP的嵌入式系统的运行效率.
基金supported by US-China Clean Energy Research Collaboration:Collaboration on Cutting-edge Technology Development of Electric Vehicle(Program of International S&T Cooperation,Grant No.2010DFA72760)
文摘The existing research of the acceleration control mainly focuses on an optimization of the velocity trajectory with respect to a criterion formulation that weights acceleration time and fuel consumption.The minimum-fuel acceleration problem in conventional vehicle has been solved by Pontryagin's maximum principle and dynamic programming algorithm,respectively.The acceleration control with minimum energy consumption for battery electric vehicle(EV)has not been reported.In this paper,the permanent magnet synchronous motor(PMSM)is controlled by the field oriented control(FOC)method and the electric drive system for the EV(including the PMSM,the inverter and the battery)is modeled to favor over a detailed consumption map.The analytical algorithm is proposed to analyze the optimal acceleration control and the optimal torque versus speed curve in the acceleration process is obtained.Considering the acceleration time,a penalty function is introduced to realize a fast vehicle speed tracking.The optimal acceleration control is also addressed with dynamic programming(DP).This method can solve the optimal acceleration problem with precise time constraint,but it consumes a large amount of computation time.The EV used in simulation and experiment is a four-wheel hub motor drive electric vehicle.The simulation and experimental results show that the required battery energy has little difference between the acceleration control solved by analytical algorithm and that solved by DP,and is greatly reduced comparing with the constant pedal opening acceleration.The proposed analytical and DP algorithms can minimize the energy consumption in EV's acceleration process and the analytical algorithm is easy to be implemented in real-time control.
