Path planning for EVs based on RA-RRT* model - Muhammad, Said; Zhou, Yimin (Frontiers in Energy Research, 2023)
The optimal path planning for EVs (Electric Vehicles) has gained much attention during the last decade due to the no pollution emission characteristics and limited power capacity of EVs batteries. In this paper, an optimal route search is proposed considering multiple charging stations in urban dynamic environment, while it is still applicable when the initial available amount of the battery fails to cover certain travel range. The TRDP (Transit Route Design Problem) and TNDP (Transit Node Design Problem) are utilized to search the most feasible routes based on the time and driving range via the improved route assisted rapid random tree (RA-RRT*) algorithm. Considering the status of charge of EVs battery during optimal routes search, three states are investigated between the destination and the aggregators: (i)Bypassing the aggregators, (ii)Stopping over a single aggregator and (iii)Stopping over multiple aggregators, whereas during the states (ii) and (iii), it requires the EVs to be charged at the charging stations obtained by RA-RRT* algorithm during approaching destination. The proposed algorithm is tested on a random data set under certain conditions, i.e., traffic flow with congestion and assigned target locations from a given map data, with the comparison experiments for efficacy verification.