A 3-D Multi-Object Path Planning Method for Electric Vehicle Considering the Energy Consumption and Distance

被引:16
|
作者
Huang, Guoming [1 ]
Yuan, Xiaofang [1 ]
Shi, Ke [1 ]
Liu, Zhixian [1 ]
Wu, Xiru [2 ]
机构
[1] Hunan Univ, Coll Elect & Informat Engn, Changsha 410082, Hunan, Peoples R China
[2] Guilin Univ Elect Technol, Sch Elect Engn & Automat, Guilin 541004, Peoples R China
基金
中国国家自然科学基金;
关键词
Path planning; cruising range; electric vehicle; multi-object optimization; chaos optimization; HYBRID ALGORITHM; NSGA-II; OPTIMIZATION; POWER; SEARCH;
D O I
10.1109/TITS.2021.3071319
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
The poor cruising range of electric vehicle (EV) is a problem preventing its popularity. To tackle this problem, methods such us battery technology, energy-based motion control technology are developed. This paper proposes a new solution from the perspective of path planning. Such a solution is called 3-D multi-object path planning method (3D-M method), in which both the energy consumption and distance are considered. The 3D-M method mainly realizes multi-object path planning by an energy consumption estimation model (ECEM) and a distance-integrated estimation model (DIEM). The ECEM can estimate the energy consumption between the neighbour position and the destination on the 3-D map, using a novel slope energy model considering energy consumption characteristic of the EV. The DIEM can estimate the integrated distance which includes the corresponding 2-D distance and 3-D distance, respectively. In the planning process, the outputs of ECEM and DIEM are combined to determine the cost of a path. In addition, a chaos-based multi-object optimizer (CBMOO) is used to search the optimal weights for the 3D-M method. The simulation experiments prove that the proposed method can generate an optimal path which saves much energy in comparison with the path provided by the distance-based method.
引用
收藏
页码:7508 / 7520
页数:13
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