系统效率最优的功率分流式混合动力汽车非线性预测控制

Nonlinear predictive control of power split hybrid electric vehicle with optimal system efficiency

针对一种基于双行星排构型的功率分流式混合动力汽车,建立系统动态模型,准确描述其转速转矩耦合关系,通过建立各部件的效率模型,分析不同模式下系统的工作效率.设计控制器结构框架,以系统工作效率和电池充放电平衡为目标,构建基于模型预测控制的优化问题,采用一步马尔科夫链模型预测驾驶员需求转矩及车速,将有限时域内的优化问题转化为非线性规划问题,基于序列二次规划算法实现优化求解.仿真研究表明,基于系统效率最优的预测控制器能够维持电池的充放电平衡,在美国城市驾驶循环(UDDS)下,当电池初始电池荷电状态(SOC)分别为0.50、0.55和0.60时,相较于以发动机燃油消耗最优为目标,车辆等效燃油经济性分别提高了7.17%、5.73%和10.11%,验证了控制器的有效性和优越性.

A dynamical model of the power split powertrain was established to accurately describe the torque and speed coupling relations within the system, aiming at a novel power split hybrid electric vehicle(HEV) with dual planetary gear sets. By means of building the efficiency model of different components, the system operation efficiency under different modes was analyzed. Then, the control framework of the proposed vehicle was designed,and the optimal control problem based on model predictive control scheme was constructed. The one-step Markov chain model was applied to predict the required driver torque and vehicle velocity. The optimal problem in the prediction horizon was converted to nonlinear programming problem, and sequential quadratic programming(SQP)was applied to derive the optimal control sequence. Simulation results demonstrate that the proposed strategy can maintain the battery charging sustainability. When the initial battery state of charge(SOC) is 0.50, 0.55 and 0.60,respectively, compared with the nonlinear predictive control with the engine fuel consumption as objective, the vehicle equivalent fuel economy is improved by 7.17%、5.73% and 10.11%, respectively, with the proposed strategy under urban dynamometer driving schedule(UDDS). Thus, the feasibility and superiority of the controller are validated.