Hybrid genetic algorithm-based optimization of powertrain and control parameters of plug-in hybrid electric bus

动力传动系统 模拟退火 地铁列车时刻表 人口 遗传算法 全局优化 工程类 行驶循环 渡线 计算机科学 数学优化 汽车工程 电动汽车 算法 数学 扭矩 物理 操作系统 社会学 人口学 人工智能 功率(物理) 热力学 量子力学
作者
Liang Li,Yahui Zhang,Chi Yang,Xiaohong Jiao,Lipeng Zhang,Jian Song
出处
期刊:Journal of The Franklin Institute-engineering and Applied Mathematics [Elsevier BV]
卷期号:352 (3): 776-801 被引量:69
标识
DOI:10.1016/j.jfranklin.2014.10.016
摘要

This paper proposes a novel hybrid genetic algorithm for the simultaneous optimization of the powertrain and control parameters in plug-in hybrid electric bus (PHEB) with trade-off between economy and dynamic performance. PHEBs are potential public transportations to alleviate energy shortages and urban environment pollution. The PHEB powertrain and control parameters significantly impact the vehicle performance and economy, and an optimization process is needed to design a set of optimized parameters for a given driving route. A novel hybrid genetic algorithm (HGA) which combines an enhanced genetic algorithm (EGA) with simulated annealing (SA) is proposed in this paper. By merging EGA with SA, simulated annealing process is applied to the better half population after EGA operations, and then an adaptive cooling schedule is introduced. In addition, several techniques are implemented to achieve the goals of sustaining the convergence capacity and maintaining diversity in the population, such as orthogonal design method, adaptive mechanisms of crossover and mutation probabilities. A solution relative error distance is defined to express the performance of standard genetic algorithm (SGA), EGA, and HGA. The optimization is performed over the following two driving cycles: (1) a driving cycle CYC_873 collected from a real bus route; and (2) Urban Dynamometer Driving Schedule+China Typical Urban Driving Cycle (UDDS+CTUDC). Simulation results indicate that the convergence speed and global searching ability of HGA are significantly better for optimal PHEB powertrain and control parameters design. And the optimal parameters might obtain the best comprehensive performance of PHEB for the given Chinese urban driving cycles.

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
孙夕然发布了新的文献求助10
刚刚
1秒前
酷波er应助别偷我增肌粉采纳,获得10
1秒前
2秒前
yinyue发布了新的文献求助10
2秒前
3秒前
美满的曼寒完成签到,获得积分10
3秒前
hikh发布了新的文献求助10
3秒前
罗静完成签到,获得积分10
5秒前
5秒前
5秒前
6秒前
7秒前
桐桐应助刻苦的如霜采纳,获得10
7秒前
qin希望应助孙夕然采纳,获得10
7秒前
情怀应助孙夕然采纳,获得10
7秒前
121314wld发布了新的文献求助10
8秒前
科研小贩完成签到,获得积分10
8秒前
核桃发布了新的文献求助10
8秒前
8秒前
8秒前
糕糕完成签到,获得积分10
8秒前
zjx完成签到,获得积分10
9秒前
汉堡包应助Chen采纳,获得10
10秒前
10秒前
小二郎应助万业t采纳,获得10
10秒前
11秒前
量子星尘发布了新的文献求助10
11秒前
shihangZhang发布了新的文献求助10
11秒前
11秒前
12秒前
严怜梦发布了新的文献求助10
12秒前
Hello应助迅速的鹤采纳,获得100
12秒前
12秒前
paradox关注了科研通微信公众号
13秒前
鲸落完成签到,获得积分10
13秒前
13秒前
小芭乐发布了新的文献求助10
13秒前
14秒前
啊沙发上发完成签到,获得积分10
14秒前
高分求助中
Picture Books with Same-sex Parented Families: Unintentional Censorship 700
ACSM’s Guidelines for Exercise Testing and Prescription, 12th edition 500
Nucleophilic substitution in azasydnone-modified dinitroanisoles 500
不知道标题是什么 500
Indomethacinのヒトにおける経皮吸収 400
Phylogenetic study of the order Polydesmida (Myriapoda: Diplopoda) 370
Effective Learning and Mental Wellbeing 300
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 遗传学 基因 物理化学 催化作用 冶金 细胞生物学 免疫学
热门帖子
关注 科研通微信公众号,转发送积分 3974943
求助须知:如何正确求助?哪些是违规求助? 3519467
关于积分的说明 11198482
捐赠科研通 3255728
什么是DOI,文献DOI怎么找? 1797904
邀请新用户注册赠送积分活动 877261
科研通“疑难数据库(出版商)”最低求助积分说明 806224