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Effect of Powertrain Design Optimisation Methodologies on Battery System Efficiency of a Hybrid Electric Vehicle

机译:动力系设计优化方法对混合动力电动汽车电池系统效率的影响

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Battery sizing has significant importance for the performance of hybrid electric vehicles (HEVs). Although several research has been done over the years for the battery sizing, no research has focused on battery system efficiency which affects fuel economy. This paper has investigated battery system efficiencies of different optimum battery sizes which were optimised using two design optimisation methodologies. The first methodology considered a single driving pattern at a time, whereas, the second methodology considered different driving patterns simultaneously for the optimisation. The study considered a simulation model of a power-split HEV for the optimisation of battery size along with internal combustion engine, motor, and generator. An electric-assist charge sustaining supervisory control strategy was considered as the energy management. The maximum speed, acceleration, and gradeability were considered as design constraints. The optimisation was carried out using a genetic algorithm. Fuel economy was considered as an objective for the optimisation. Five standard driving patterns of different traffic conditions and driving styles were considered for the optimisation. Battery system efficiency of each optimum design was calculated over five standard driving patterns. This study found that battery system efficiency of the design which was optimised over different driving patterns was on average 2% higher compared to that of the designs which were optimised over a single driving pattern. This study shows a direction for the selection of battery size in HEVs for real-world application.
机译:电池尺寸对混合动力电动车(HEV)的性能具有重要意义。虽然多年来已经进行了几个研究,但对于电池施胶,没有研究专注于影响燃油经济性的电池系统效率。本文研究了使用两种设计优化方法优化的不同最佳电池尺寸的电池系统效率。第一方法是一次考虑单个驾驶模式,而第二种方法同时考虑了不同的驾驶模式。该研究认为,用于优化电池尺寸以及内燃机,电动机和发电机的电池尺寸的仿真模型。电气辅助费用维持监督控制策略被视为能源管理。最大速度,加速度和渐变性被认为是设计约束。使用遗传算法进行优化。燃油经济被认为是优化的目标。考虑了5种不同交通条件和驱动风格的标准驾驶模式进行了优化。每个最佳设计的电池系统效率在五个标准驾驶模式下计算。该研究发现,与通过单个驱动图案优化的设计相比,通过不同的驱动图案优化的设计的电池系统效率平均高出2%。本研究显示了在HEVS中选择电池尺寸的方向,用于真实世界的应用。

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