Finding the optimal reliable energy consumption path for electric vehicles under rainfall conditions

ABSTRACT

This paper presents a new path-finding problem to ensure reliable energy consumption for electric vehicles (EVs) under rainfall conditions. The objective function of the proposed model aims to find a reliable path that minimises energy consumption while ensuring a certain probability of completing the trip without exhausting a given battery energy budget. By considering the influence of adverse weather conditions at different periods, the existing model is expanded. To address the non-additivity and non-linearity characteristics of the optimisation model, an enhanced heuristic algorithm is proposed, incorporating inequality techniques, the K-shortest algorithm, and path-updating strategies. Lastly, the proposed algorithm is validated using Hong Kong’s grid-based road network as a case study, which demonstrates the correctness and effectiveness of the algorithm. The results indicate that by considering adverse weather conditions, the estimation of energy consumption can be significantly improved in terms of accuracy, achieving more efficient and reliable optimal path recommendations.

KEYWORDS:

• Electric vehicles
• reliable energy consumption path
• network uncertainties
• adverse weather conditions

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This research was supported by the National Natural Science Foundation of China [grant number 72301236, 72071202 and 72204210], the Mathematics Tianyuan Fund of the National Natural Science Foundation of China [grant number 12326315, 12326321], Natural Science Foundation of Jiangsu Province (Project No. BK20230678), Humanities and Social Sciences Youth Foundation, Ministry of Education of the People’s Republic of China (Project No. 22YJCZH144), General Project of Natural Science Foundation of Colleges and Universities in Jiangsu Province (Project No. 22KJB110027).