混合动力车辆的能量管理策略对提高燃油经济性十分重要． 为了提高功率分流 式混合动力车辆的燃油经济性以及能量管理策略的实时性，设计了基于显式随机模型预 测控制的能量管理策略． 首先利用马尔科夫链预测车速，通过简化控制模型，把非线性的 能量管理问题转化为线性二次优化问题，建立了以预测域内能量消耗最小为目标的随机 模型预测策略(SMPC);然后通过参数化求解得到显式随机模型预测控制策略，该策略既 保持了随机模型预测控制方法的优势，又提高了计算速度;最后在多个工况下进行仿真， 对提出的能量管理策略的有效性进行验证． 仿真结果表明:与基于规则的控制策略相比燃 油经济性最高可提高 28． 64%，同时该策略在仿真中的平均计算时间为 3． 1ms，具有实时 运算潜力．

Energy management strategies are important for hybrid electric vehicles to improve fuel economy． In or- der to improve the fuel economy of power split hybrid vehicles and the real-time performance of energy management strategies，an energy management strategy based on explicit stochastic model predictive control was designed． Firstly，the Markov chain was used to predict the vehicle speed． Then by simplifying the control model and trans- forming the nonlinear energy management problem into a linear quadratic optimization problem，a stochastic model prediction strategy (SMPC) with the minimum energy consumption in the prediction domain was established． Sec- ondly，the explicit stochastic model prediction strategy is obtained by solving the problem parametrically，and this strategy not only maintained the advantages of the stochastic model predictive control method，but also improved the calculation speed． Finally，the simulation is carried out under multiple working conditions to verify the effec- tiveness of the proposed energy management strategy． The simulation results show that fuel economy can be in- creased by up to 28. 64% compared to rule-based control strategies，and the average calculation time in the simu- lation is 3. 1ms，which indicate that the strategy has real-time computing potential．