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Energy minimization for an electric bus using a genetic algorithm

Sina Torabi, Mauro Bellone, Mattias Wahde

2020European Transport Research Review27 citationsDOIOpen Access PDF

Abstract

Abstract Background and methods This paper addresses, in simulation, energy minimization of an autonomous electric minibus operating in an urban environment. Two different case studies have been considered, each involving a total of 10 different 2?km bus routes and two different average speeds. In the proposed method, the minibus follows an optimized speed profile, generated using a genetic algorithm. Results In the first case study the vehicle was able to reduce its energy consumption by around 7 to 12% relative to a baseline case in which it maintains a constant speed between stops, with short acceleration and deceleration phases. In the second case study, involving mass variation (passengers entering and alighting) it was demonstrated that the number of round trips that can be completed on a single battery charge is increased by around 10% using the proposed method.

Topics & Concepts

MinificationGenetic algorithmAccelerationEnergy (signal processing)Battery (electricity)Energy consumptionEnergy minimizationSimulationAutomotive engineeringElectric vehicleAlgorithmEngineeringComputer scienceReal-time computingControl theory (sociology)Mathematical optimizationPower (physics)MathematicsStatisticsElectrical engineeringPhysicsArtificial intelligenceClassical mechanicsQuantum mechanicsControl (management)Electric and Hybrid Vehicle TechnologiesElectric Vehicles and InfrastructureAdvanced Battery Technologies Research
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