针对氢燃料电池大功率电机驱动系统,提出一种以燃料电池为主动力源的轻量化级联H桥(cascadedH-bridge,CHB)型混合动力中压电机调速系统。所提系统由燃料电池/蓄电池/超级电容的混合动力源供电,基于四有源桥(quad activebridge,QAB)与CH...针对氢燃料电池大功率电机驱动系统,提出一种以燃料电池为主动力源的轻量化级联H桥(cascadedH-bridge,CHB)型混合动力中压电机调速系统。所提系统由燃料电池/蓄电池/超级电容的混合动力源供电,基于四有源桥(quad activebridge,QAB)与CHB子模块互联的两级变换器(cascaded H-bridges with quad active bridge,CHB-QAB)作为调速变换器。CHB-QAB通过四绕组高频变压器将各子模块进行内部互联,采用单边同步双边移相调制的策略,使得所有子模块呈现开关电容特性,在不依赖复杂控制的前提下,减小子模块电容的容值,提升系统的功率密度。针对三类动力源,采用基于低通滤波(lowpassfilter,LPF)的能量管理策略,保证电机实际运行过程中的有效功率分配,解决燃料电池对电机动态响应缓慢和燃料饥饿现象等问题。最后通过仿真与实验对所提轻量化电机调速系统进行验证。展开更多
An inverse system method based optimal control strategy was proposed for the shunt hybrid active power filter （SHAPF） to enhance its harmonic elimination performance. Based on the inverse system method, the d-axis a...An inverse system method based optimal control strategy was proposed for the shunt hybrid active power filter （SHAPF） to enhance its harmonic elimination performance. Based on the inverse system method, the d-axis and q-axis current dynamics of the SHAPF system were decoupled and linearized into two pseudolinear subsystems. Then, an optimal feedback controUer was designed for the pseudolinear system, and the stability condition of the resulting zero dynamics was presented. Under the control strategy, the current dynamics can asymptotically converge to their reference states and the zero dynamics can be bounded. Simulation results show that the proposed control strategy is robust against load variations and system parameter mismatches, its steady-state performance is better than that of the traditional linear control strategy.展开更多
With the development of fast communication technology between ego vehicle and other traffic participants,and automated driving technology,there is a big potential in the improvement of energy efficiency of hybrid elec...With the development of fast communication technology between ego vehicle and other traffic participants,and automated driving technology,there is a big potential in the improvement of energy efficiency of hybrid electric vehicles(HEVs).Moreover,the terrain along the driving route is a non-ignorable factor for energy efficiency of HEV running on the hilly streets.This paper proposes a look-ahead horizon-based optimal energy management strategy to jointly improve the efficiencies of powertrain and vehicle for connected and automated HEVs on the road with slope.Firstly,a rule-based framework is developed to guarantee the success of automated driving in the traffic scenario.Then a constrained optimal control problem is formulated to minimize the fuel consumption and the electricity consumption under the satisfaction of inter-vehicular distance constraint between ego vehicle and preceding vehicle.Both speed planning and torque split of hybrid powertrain are provided by the proposed approach.Moreover,the preceding vehicle speed in the look-ahead horizon is predicted by extreme learning machine with real-time data obtained from communication of vehicle-to-everything.The optimal solution is derived through the Pontryagin’s maximum principle.Finally,to verify the effectiveness of the proposed algorithm,a traffic-in-the-loop powertrain platform with data from real world traffic environment is built.It is found that the fuel economy for the proposed energy management strategy improves in average 17.0%in scenarios of different traffic densities,compared to the energy management strategy without prediction of preceding vehicle speed.展开更多
文摘针对氢燃料电池大功率电机驱动系统,提出一种以燃料电池为主动力源的轻量化级联H桥(cascadedH-bridge,CHB)型混合动力中压电机调速系统。所提系统由燃料电池/蓄电池/超级电容的混合动力源供电,基于四有源桥(quad activebridge,QAB)与CHB子模块互联的两级变换器(cascaded H-bridges with quad active bridge,CHB-QAB)作为调速变换器。CHB-QAB通过四绕组高频变压器将各子模块进行内部互联,采用单边同步双边移相调制的策略,使得所有子模块呈现开关电容特性,在不依赖复杂控制的前提下,减小子模块电容的容值,提升系统的功率密度。针对三类动力源,采用基于低通滤波(lowpassfilter,LPF)的能量管理策略,保证电机实际运行过程中的有效功率分配,解决燃料电池对电机动态响应缓慢和燃料饥饿现象等问题。最后通过仿真与实验对所提轻量化电机调速系统进行验证。
基金Project(61174068)supported by the National Natural Science Foundation of China
文摘An inverse system method based optimal control strategy was proposed for the shunt hybrid active power filter （SHAPF） to enhance its harmonic elimination performance. Based on the inverse system method, the d-axis and q-axis current dynamics of the SHAPF system were decoupled and linearized into two pseudolinear subsystems. Then, an optimal feedback controUer was designed for the pseudolinear system, and the stability condition of the resulting zero dynamics was presented. Under the control strategy, the current dynamics can asymptotically converge to their reference states and the zero dynamics can be bounded. Simulation results show that the proposed control strategy is robust against load variations and system parameter mismatches, its steady-state performance is better than that of the traditional linear control strategy.
文摘With the development of fast communication technology between ego vehicle and other traffic participants,and automated driving technology,there is a big potential in the improvement of energy efficiency of hybrid electric vehicles(HEVs).Moreover,the terrain along the driving route is a non-ignorable factor for energy efficiency of HEV running on the hilly streets.This paper proposes a look-ahead horizon-based optimal energy management strategy to jointly improve the efficiencies of powertrain and vehicle for connected and automated HEVs on the road with slope.Firstly,a rule-based framework is developed to guarantee the success of automated driving in the traffic scenario.Then a constrained optimal control problem is formulated to minimize the fuel consumption and the electricity consumption under the satisfaction of inter-vehicular distance constraint between ego vehicle and preceding vehicle.Both speed planning and torque split of hybrid powertrain are provided by the proposed approach.Moreover,the preceding vehicle speed in the look-ahead horizon is predicted by extreme learning machine with real-time data obtained from communication of vehicle-to-everything.The optimal solution is derived through the Pontryagin’s maximum principle.Finally,to verify the effectiveness of the proposed algorithm,a traffic-in-the-loop powertrain platform with data from real world traffic environment is built.It is found that the fuel economy for the proposed energy management strategy improves in average 17.0%in scenarios of different traffic densities,compared to the energy management strategy without prediction of preceding vehicle speed.
