A Quantum Approach to the Problem of Charging Electric Cars on a Motorway

In this paper, the problem of charging electric motor vehicles on a motorway is considered. Charging points are located alongside the motorway. It is assumed that there are a number of vehicles on a given section of a motorway. In the motorway, there are several nodes, and for each vehicle, the entering and the leaving nodes are known, as well as the time of entrance. For each vehicle, we know the total capacity of its battery, and the current amount of energy in the battery when entering the motorway. It is also assumed that for each vehicle, there is a finite set of speeds it can use when traveling the motorway. The speed is chosen when entering the motorway, and cannot be changed before reaching the charging station. For each speed, there is given a corresponding power usage; the higher the speed, the larger the power usage. Each vehicle can only use one charger, and when its battery is full, the amount of energy is sufficient for reaching the outgoing node. We look for a feasible solution to the problem, i.e., a solution in which no vehicle has to wait for a charger. The problem is formulated as a problem of scheduling independent, nonpreemptable jobs in parallel, unrelated machines under an additional doubly constrained resource, which is power. Quantum approaches to solve the defined problem are proposed. They use the quantum approximate optimization algorithm and the quantum annealing technique. A computational experiment is presented and discussed. Some conclusions and directions for future research are given.

[1]  I. Mahdavi,et al.  Scheduling unrelated parallel machine problem with multi-mode processing times and batch delivery cost , 2022, OPSEARCH.

[2]  M. Mitici,et al.  Electric flight scheduling with battery-charging and battery-swapping opportunities , 2022, EURO J. Transp. Logist..

[3]  G. Raidl,et al.  Smart Charging of Electric Vehicles Considering SOC-Dependent Maximum Charging Powers , 2021, Energies.

[4]  J. Józefowska,et al.  Scheduling UAV’s on Autonomous Charging Station , 2021, Modern Technologies Enabling Safe and Secure UAV Operation in Urban Airspace.

[5]  Piotr Sawicki,et al.  Multiple-Criteria-Based Electric Vehicle Charging Infrastructure Design Problem , 2021, Energies.

[6]  Gang Xin,et al.  Noise‐enhanced quantum annealing approach and its application in plug‐in hybrid electric vehicle charging optimization , 2021, Electronics Letters.

[7]  Fengqi You,et al.  Quantum computing for energy systems optimization: Challenges and opportunities , 2019, Energy.

[8]  Travis S. Humble,et al.  Application of Quantum Annealing to Nurse Scheduling Problem , 2019, Scientific Reports.

[9]  Na Li,et al.  Optimal Scheduling of Battery Charging Station Serving Electric Vehicles Based on Battery Swapping , 2019, IEEE Transactions on Smart Grid.

[10]  Stuart Hadfield,et al.  On the Representation of Boolean and Real Functions as Hamiltonians for Quantum Computing , 2018, ACM Transactions on Quantum Computing.

[11]  Youxian Sun,et al.  Optimal Charging Schedule for a Battery Switching Station Serving Electric Buses , 2016, IEEE Transactions on Power Systems.

[12]  Thomas Bräunl,et al.  Driving electric vehicles at highway speeds: The effect of higher driving speeds on energy consumption and driving range for electric vehicles in Australia , 2016 .

[13]  Hans-Arno Jacobsen,et al.  Smart Charging Schedules for Highway Travel With Electric Vehicles , 2016, IEEE Transactions on Transportation Electrification.

[14]  Shun-Neng Yang,et al.  Charge scheduling of electric vehicles in highways , 2013, Math. Comput. Model..

[15]  I. Chuang,et al.  Quantum Computation and Quantum Information: Bibliography , 2010 .

[16]  A. Kitaev Quantum computations: algorithms and error correction , 1997 .

[17]  Malgorzata Sterna,et al.  Handbook on Scheduling , 2007 .