基于改进算法GOA和GA的电动汽车动力总成混合能量双存储系统

B. Pattanaik, Mukil Alagirisamy
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引用次数: 1

摘要

尽管电动汽车有许多优点,比如对地形友好、噪音小、减少对无功功率的依赖,但它也有明显的缺点。通过电池和超级电容器的集成,将同时获得电动汽车的大功率和高能动力系统。因此,超级电容器管理短期电力需求,而电池为车辆提供长期移动性。将GOA算法与遗传算法相结合,提出了一种新的算法——冷纯种GOA-GA。所提出的混合GOA-GA算法在达到收敛性的同时,有较强的脱离原最优点的可能性。采用该算法进行多目标函数优化,降低HESS质量,提高车辆行驶里程。通过使用MATLAB/ Goad软件,整个框架与FTP-75, US06(最大速度以及所需加速度)和HWFET驱动周期一起建立。与具有单个HESS单元的等效电动汽车相比,所提出的二元HESS电枢在降低HESS质量的同时增加了行驶里程。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Hybrid Energy Dual Storage Systems for EV Powertrain with Enhanced Algorithm GOA and GA
Although EV offers several advantages such as being terrain friendly, producing less noise, and reducing dependency on reactive powers, it also has significant drawbacks. High power and high energy force systems for EVs will be obtained concurrently through the integration of batteries and ultra-capacitors. As a result, ultra-capacitors manage short-term power demands, while batteries provide long-term mobility for the vehicle. A novel algorithm, cold-thoroughbred GOA-GA, is proposed by combining the GOA and GA. The proposed hybrid GOA-GA has a strong eventuality to escape original optima while achieving the convergence. The proposed crossbred algorithm is used to perform a multi-objective function optimization to drop the HESS mass as well as increase the vehicle's operating range. By exercising the MATLAB/ Goad software, the entire frame was erected with the FTP-75, US06 (maximum speed as well as demanded acceleration) and HWFET driving cycles. When compared to an equivalent EV posted with a single HESS unit, the proposed binary-HESS armature has increased driving range while lowering the HESS mass.
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