A Novel Energy-Efficiency Optimization Approach Based on Driving Patterns Styles and Experimental Tests for Electric Vehicles

• Main Authors: Juan Diego Valladolid, Diego Patino, Giambattista Gruosso, Carlos Adrián Correa-Flórez, José Vuelvas, Fabricio Espinoza
• Format: Article
• Language: English
• Published: MDPI AG 2021-05-01
• Series: Electronics
• Subjects: electrical vehicle; energy management; system efficiency; optimization of driving patterns; particle swarm optimization algorithm
• Online Access: https://www.mdpi.com/2079-9292/10/10/1199

This article proposes an energy-efficiency strategy based on the optimization of driving patterns for an electric vehicle (EV). The EV studied in this paper is a commercial vehicle only driven by a traction motor. The motor drives the front wheels indirectly through the differential drive. The electrical inverter model and the power-train efficiency are established by lookup tables determined by power tests in a dynamometric bank. The optimization problem is focused on maximizing energy-efficiency between the wheel power and battery pack, not only to maintain but also to improve its value by modifying the state of charge (SOC). The solution is found by means of a Particle Swarm Optimization (PSO) algorithm. The optimizer simulation results validate the increasing efficiency with the speed setpoint variations, and also show that the battery SOC is improved. The best results are obtained when the speed variation is between 5% and 6%.