To save money or to save time: Intelligent routing design for plug-in hybrid electric vehicle |
| |
| Institution: | 1. Northwestern Polytechnical University, Xi’an, China;2. McGill University, Montreal, Canada;1. Department of Physics, Payame Noor University, P.O.Box 19395-3697 Tehran, Islamic Republic of Iran;2. Department of Physics, Azarbaijan Shahid Madani University, PO Box 51745-406 Tabriz, Islamic Republic of Iran;3. Department of Mathematics, Payame Noor University, P.O.Box 19395-3697 Tehran, Islamic Republic of Iran;1. Interuniversity Research Centre on Enterprise Networks, Logistics and Transportation (CIRRELT), Université Laval, 2325, Rue de la Terrasse, Quebec G1V 0A6, Canada;2. Department of Economics and Management, University of Brescia, Brescia, Italy;3. Canada Research Chair in Integrated Logistics and Interuniversity Research Centre on Enterprise Networks, Logistics and Transportation (CIRRELT), Universite Laval, 2325, Rue de la Terrasse, Quebec G1V 0A6, Canada;1. Operations Research and Logistics Group, Wageningen University, De Leeuwenborch (building 201), Hollandseweg 1, 6706 KN Wageningen, The Netherlands;2. Southampton Business School and Centre for Operational Research, Management Science and Information Systems (CORMSIS), University of Southampton, Southampton, Highfield SO17 1BJ, United Kingdom;1. Department of Electrical Engineering, University of Engineering and Technology, Peshawar, Pakistan;2. Department of Electronics Engineering, Capital University of Science and Technology, Islamabad, Pakistan;3. Department of Electrical Engineering, UMT Lahore, Sialkot Campus, Pakistan;4. Faculty of Electrical Energy System Engineering, U.S. Pakistan Center for Advanced Studies in Energy UET, Peshawar, Pakistan;5. Department of Electronics Engineering, International Islamic University, Islamabad, Pakistan;6. Department of Electrical Engineering, FAST, Islamabad, Pakistan |
| |
| Abstract: | Electric vehicles (EVs) are promising alternative to conventional vehicles, due to their low fuel cost and low emissions. As a subset of EVs, plug-in hybrid electric vehicles (PHEVs) backup batteries with combustion engines, and thus have a longer traveling range than battery electric vehicles (BEVs). However, the energy cost of a PHEV is higher than a BEV because the gasoline price is higher than the electricity price. Hence, choosing a route with more charging opportunities may result in less fuel cost than the shortest route. Different with the traditional shortest-path and shortest-time routing methods, we propose a new routing choice with the lowest fuel cost for PHEV drivers. Existing algorithms for gasoline vehicles cannot be applied because they never considered the regenerative braking which may result in negative energy consumption on some road segments. Existing algorithms for BEVs are not competent too because PHEVs have two power sources. Thus, even if along the same route, different options of power source will lead to different energy consumption. This paper proposes a cost-optimal algorithm (COA) to deal with the challenges. The proposed algorithm is evaluated using real-world maps and data. The results show that there is a trade-off between traveling cost and time consumed when driving PHEVs. It is also observed that the average detour rate caused by COA is less than 14%. Significantly, the algorithm averagely saves more than 48% energy cost compared to the shortest-time routing. |
| |
| Keywords: | PHEV Routing Navigation Energy Charging Cost |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
