Battery SOC constraint comparison for predictive energy management of plug-in hybrid electric bus
Battery SOC constraint comparison for predictive energy management of plug-in hybrid electric bus
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DOI：
10.1016/j.apenergy.2016.09.071
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发表时间：
2017-05
期刊：
影响因子：
11.2
通讯作者：
Gaopeng Li;Jieli Zhang;Hongwen He
中科院分区：
文献类型：
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作者：
Gaopeng Li;Jieli Zhang;Hongwen He
采用模型预测控制（MPC）方法解决了插电式混合动力客车（PHEB）的能量管理问题。动态规划（DP）作为一种全局优化方法，在MPC的每个时间步插入，以解决与预测范围相关的优化问题。建立了多步马尔可夫预测模型，预测MPC的近期行驶速度。电池SOC被抑制在参考轨迹附近波动，以确保MPC的全局性能。本文提出了三种新的抑制方法，并进行了比较。对不同SOC约束方式下的燃油经济性进行了评价。仿真结果表明，通过自适应地约束电池SOC，MPC策略具有最佳的燃油经济性，燃油消耗量比规则控制策略减少8.7%。
In this paper, model predictive control (MPC) is employed to resolve the energy management problem of a plug-in hybrid electric bus (PHEB). Dynamic programming (DP), as a global optimization method, is inserted at each time step of the MPC, to solve the optimization problem regarding the prediction horizon. A multi-step Markov prediction model is constructed to forecast the near future driving velocities for the MPC. The battery SOC is restrained to fluctuate near a reference trajectory to ensure the global performance of MPC. Three novel restraining methods are proposed and compared in this paper. The resultant fuel economy performance with different SOC constraint methods are evaluated. Simulation results indicate that by restraining the battery SOC adaptively to the control variables gains the best fuel economy performance, and the fuel consumption of MPC is 8.7% less than a ruled based strategy.