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Rule based energy management strategy for a series-parallel plug-in hybrid electric bus optimized by dynamic programming

机译:通过动态编程优化串联-并联插电式混合动力电动客车的基于规则的能量管理策略

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An appropriate energy management strategy is able to further improve the fuel economy of PHEVs. The rule-based energy management algorithms are dominated in industry due to their fast computation and ease of establishment potentials, however, their performance differ a lot from improper setting of parameters and control actions. This paper employs the dynamic programming (DP) to locate the optimal actions for the engine in PHEVs, and more importantly, proposes a recalibration method to improve the performance of the rule-based energy management through the results calculated by DP algorithm. Eventually, an optimization-based rule development procedure is presented and further validated by hardware-in-loop (HIL) simulation experiments. The HIL simulation results show that, the improved rule-based energy management strategy reduces fuel consumption per 100 km from 25.46 L diesel to 22.80 L diesel. The main contribution of this study is to explore a novel way to calibrate the existed heuristic control strategy with the global optimization result through advanced intelligent algorithms. (C) 2015 Elsevier Ltd. All rights reserved.
机译:适当的能源管理策略能够进一步改善插电式混合动力汽车的燃油经济性。基于规则的能源管理算法由于其快速的计算和易于建立的潜力而在工业中占主导地位,但是,其性能与参数和控制动作的不正确设置有很大不同。本文采用动态规划(DP)来定位PHEV中发动机的最佳动作,更重要的是,提出了一种重新校准方法,以通过DP算法计算的结果提高基于规则的能源管理的性能。最终,提出了一种基于优化的规则开发程序,并通过硬件在环(HIL)仿真实验对其进行了进一步验证。 HIL仿真结果表明,改进的基于规则的能源管理策略将每100公里的燃油消耗从25.46升柴油降低到22.80升柴油。这项研究的主要贡献是探索一种通过先进的智能算法以全局优化结果校准现有启发式控制策略的新方法。 (C)2015 Elsevier Ltd.保留所有权利。

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