Chance Constrained Routing and Charging Problem of Electric Vehicles

Shibo Chen1; Canqi Yao1; Haoyu Miao1; Zhicheng Li2; Zaiyue Yang1

10.1109/CAC57257.2022.10054938

2022

2688-092X

978-1-6654-6534-2

2022 China Automation Congress (CAC)

3117-3122

25-27 Nov. 2022

Xiamen, China

Different from traditional vehicles, the routing problem of electric vehicles (EVs) is closely coupled with their charging. Hence, operating EV requires a joint optimization of both routing and charging. Moreover, the travel time and energy consumption uncertainties also bring challenges to the EV operation in practice. In this paper, we study the routing and charging problem of EVs under the chance constrained optimization framework, where uncertainties are tackled with probabilistic constraints. An iterative algorithm is proposed, which transforms the original challenging mixed-integer nonlinear program into the iteration of two linear programs. The finite convergence of this algorithm is also proved. Numerical results show that our proposed algorithm can achieve near-optimal solutions in rather short computation times.

electric vehicle routing problem chance constrained optimization iterative algorithm

第一

IEEE

1.Department of Mechanical and Energy Engineering, Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems, the Guangdong Provincial Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities, Southern University of Science and Technology, Shenzhen, China
2.Shenzhen Polytechnic, Internet of Things Research Institute, Shenzhen, China

Shibo Chen,Canqi Yao,Haoyu Miao,et al. Chance Constrained Routing and Charging Problem of Electric Vehicles[C],2022:3117-3122.