A 3-D Multi-Object Path Planning Method for Electric Vehicle Considering the Energy Consumption and Distance
Guoming Huang, Xiaofang Yuan, Ke Shi, Zhixian Liu, Xiru Wu
Abstract
The poor cruising range of electric vehicle (EV) is a problem preventing its popularity. To tackle this problem, methods such as 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.