混合动力汽车能量管理策略会影响其动力性和经济性。为了寻找整车的最优节油点及控制策略,文章基于世界轻型汽车测试循环(world light vehicle test cycle,WLTC)工况,提出了利用动态规划算法优化插电式并联混合动力汽车能量管理策略。...混合动力汽车能量管理策略会影响其动力性和经济性。为了寻找整车的最优节油点及控制策略,文章基于世界轻型汽车测试循环(world light vehicle test cycle,WLTC)工况,提出了利用动态规划算法优化插电式并联混合动力汽车能量管理策略。以发动机、电机的扭矩和角速度作为动态规划的控制变量,以保证电池荷电平衡和燃油最小为目标,建立动态规划模型。仿真结果表明,所提出的能量管理策略能使电池荷电状态(state of charge,SOC)保持在设定范围之内,且相对于基于标定经验规则的能量管理控制策略,节油率能达到5.78%,此方法对于整车厂(original equipment manufacturer,OEM)制定并联式混合动力汽车整车控制器能量控制策略及实车标定工作有一定的参考意义。展开更多
Despite the series-parallel hybrid electric vehicle inherits the performance advantages from both series and parallel hybrid electric vehicle, few researches about the series-parallel hybrid electric vehicle have been...Despite the series-parallel hybrid electric vehicle inherits the performance advantages from both series and parallel hybrid electric vehicle, few researches about the series-parallel hybrid electric vehicle have been revealed because of its complex co nstruction and control strategy. In this paper, a series-parallel hybrid electric bus as well as its control strategy is revealed, and a control parameter optimization approach using the real-valued genetic algorithm is proposed. The optimization objective is to minimize the fuel consumption while sustain the battery state of charge, a tangent penalty function of state of charge（SOC） is embodied in the objective function to recast this multi-objective nonlinear optimization problem as a single linear optimization problem. For this strategy, the vehicle operating mode is switched based on the vehicle speed, and an ＂optimal line＂ typed strategy is designed for the parallel control. The optimization parameters include the speed threshold for mode switching, the highest state of charge allowed, the lowest state of charge allowed and the scale factor of the engine optimal torque to the engine maximum torque at a rotational speed. They are optimized through numerical experiments based on real-value genes, arithmetic crossover and mutation operators. The hybrid bus has been evaluated at the Chinese Transit Bus City Driving Cycle via road test, in which a control area network-based monitor system was used to trace the driving schedule. The test result shows that this approach is feasible for the control parameter optimization. This approach can be applied to not only the novel construction presented in this paper, but also other types of hybrid electric vehicles.展开更多
文摘混合动力汽车能量管理策略会影响其动力性和经济性。为了寻找整车的最优节油点及控制策略,文章基于世界轻型汽车测试循环(world light vehicle test cycle,WLTC)工况,提出了利用动态规划算法优化插电式并联混合动力汽车能量管理策略。以发动机、电机的扭矩和角速度作为动态规划的控制变量,以保证电池荷电平衡和燃油最小为目标,建立动态规划模型。仿真结果表明,所提出的能量管理策略能使电池荷电状态(state of charge,SOC)保持在设定范围之内,且相对于基于标定经验规则的能量管理控制策略,节油率能达到5.78%,此方法对于整车厂(original equipment manufacturer,OEM)制定并联式混合动力汽车整车控制器能量控制策略及实车标定工作有一定的参考意义。
基金supported by National Hi-tech Research and Development Program of China (863 Program, Grant No. 2006AA11A127)
文摘Despite the series-parallel hybrid electric vehicle inherits the performance advantages from both series and parallel hybrid electric vehicle, few researches about the series-parallel hybrid electric vehicle have been revealed because of its complex co nstruction and control strategy. In this paper, a series-parallel hybrid electric bus as well as its control strategy is revealed, and a control parameter optimization approach using the real-valued genetic algorithm is proposed. The optimization objective is to minimize the fuel consumption while sustain the battery state of charge, a tangent penalty function of state of charge（SOC） is embodied in the objective function to recast this multi-objective nonlinear optimization problem as a single linear optimization problem. For this strategy, the vehicle operating mode is switched based on the vehicle speed, and an ＂optimal line＂ typed strategy is designed for the parallel control. The optimization parameters include the speed threshold for mode switching, the highest state of charge allowed, the lowest state of charge allowed and the scale factor of the engine optimal torque to the engine maximum torque at a rotational speed. They are optimized through numerical experiments based on real-value genes, arithmetic crossover and mutation operators. The hybrid bus has been evaluated at the Chinese Transit Bus City Driving Cycle via road test, in which a control area network-based monitor system was used to trace the driving schedule. The test result shows that this approach is feasible for the control parameter optimization. This approach can be applied to not only the novel construction presented in this paper, but also other types of hybrid electric vehicles.
