Adaptive Real-Time Energy Management Strategy for Plug-In Hybrid Electric Vehicle Based on Simplified-ECMS and a Novel Driving Pattern Recognition Method
Adaptive Real-Time Energy Management Strategy for Plug-In Hybrid Electric Vehicle Based on Simplified-ECMS and a Novel Driving Pattern Recognition Method
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基于简化ECMS和新型驾驶模式识别方法的插电式混合动力汽车自适应实时能量管理策略
DOI：
10.1155/2018/5816861
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发表时间：
2018-10
影响因子：
--
通讯作者：
Li Ming
中科院分区：
文献类型：
--
作者：
Zeng Yuping;Sheng Jing;Li Ming
针对并联式插电式混合动力汽车(PHEV)，提出了一种自适应实时能量管理策略。做了三个方面的努力。首先，提出了一种新的基于统计分析的驾驶模式识别方法。该方法将驾驶循环分为低速循环、中速循环和高速循环三种行驶模式，并对这三种驾驶模式进行统计分析，得到规则，根据这些规则可以识别实时驾驶循环的类型。其次，采用粒子群优化算法对等效因子进行优化，得到了上述三种行驶循环下以电池荷电状态(SOC)为指标、水平以行驶距离为指标的等效系数图。最后，提出了一种基于SIMPLIZED-ECMS和新型驾驶模式识别方法的自适应实时能量管理策略。对一次试驾循环进行了仿真。仿真结果表明，与基于CD-CS的自适应能量管理策略相比，自适应能量管理策略在测试行驶周期内可使PHEV的油耗降低17.63%。该自适应控制策略的计算时间明显短于基于ECMS的控制策略，接近基于CD-CS的实时控制策略。
This paper proposes an adaptive real-time energy management strategy for a parallel plug-in hybrid electric vehicle (PHEV). Three efforts have been made. First, a novel driving pattern recognition method based on statistical analysis has been proposed. This method classified driving cycles into three driving patterns: low speed cycle, middle speed cycle, and high speed cycle, and then carried statistical analysis on these three driving patterns to obtain rules; the types of real-time driving cycles can be identified according to these rules. Second, particle swarm optimization (PSO) algorithm is applied to optimize equivalent factor (EF) and then the EF MAPs, indexed vertically by battery’s State of Charge (SOC) and horizontally by driving distance, under the above three driving cycles, are obtained. Finally, an adaptive real-time energy management strategy based on Simplified-ECMS and the novel driving pattern recognition method has been proposed. Simulation on a test driving cycle is performed. The simulation results show that the adaptive energy management strategy can decrease fuel consumption of PHEV by 17.63% under the testing driving cycle, compared to CD-CS-based strategy. The calculation time of the proposed adaptive strategy is obviously shorter than the time of ECMS-based strategy and close to the time of CD-CS-based strategy, which is a real-time control strategy.
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