Shivappriya S N, Gowrishankar T, Stoian Gabriel, Anitha J, Hemanth D Jude
Department of ECE, Kumaraguru College of Technology, Coimbatore, India.
Bosch Global Software Technologies, Coimbatore, India.
Heliyon. 2025 Jan 29;11(3):e42325. doi: 10.1016/j.heliyon.2025.e42325. eCollection 2025 Feb 15.
Hybrid Electric Vehicles (HEVs) demonstrate superior fuel efficiency and reduced emissions in comparison to conventional vehicles. To further enhance the HEV performance, Powell's based Artificial Bee Colony (ABC) heuristic approach is used. Powell's ABC focuses on the improved local search ability and increased speed of convergence. The multi parameter optimization approach with the PNGV constraints for the four differently weighted objective function parameters, the experiments were carried out for most generally used driving cycles FTP, ECE-EUDC and UDDS. Compared with the initial values, the proposed approach gives the improvement in the fuel efficiency by 10.03 % and the emissions are reduced to a maximum of 18.4 % and improved overall vehicle efficiency is 11.1 % for the ECE-EUDC driving cycle. For the UDDS driving cycle, fuel efficiency can be improved by 18.2 % and the emissions are reduced to a maximum of 43.24 %, improved overall vehicle efficiency 10.1 %. For FTP driving cycle fuel economy by 39.98 % and the emissions are reduced to a maximum of 43.75 %, improved overall vehicle energy efficiency up to 11.6 %. The findings indicate that Powell's ABC approach achieves faster convergence to a notably more precise final solution across various typical driving cycles compared to conventional methods.
与传统车辆相比，混合动力电动汽车（HEV）具有更高的燃油效率和更低的排放。为了进一步提高HEV的性能，采用了基于鲍威尔法的人工蜂群（ABC）启发式方法。鲍威尔法的ABC着重于提高局部搜索能力和加快收敛速度。针对四个不同加权的目标函数参数，采用了具有PNGV约束的多参数优化方法，并针对最常用的驾驶循环FTP、ECE-EUDC和UDDS进行了实验。与初始值相比，对于ECE-EUDC驾驶循环，所提出的方法使燃油效率提高了10.03%，排放最多减少了18.4%，整体车辆效率提高了11.1%。对于UDDS驾驶循环，燃油效率可提高18.2%，排放最多减少43.24%，整体车辆效率提高10.1%。对于FTP驾驶循环，燃油经济性提高39.98%，排放最多减少43.75%，整体车辆能源效率提高至11.6%。研究结果表明，与传统方法相比，鲍威尔法的ABC方法在各种典型驾驶循环中能够更快地收敛到明显更精确的最终解。
