Transmission Design and Control Optimization of an Electric Vehicle Using Analytical Modeling Methods

This paper introduces a framework to systematically optimize the design and control of an electric vehicle transmission, connecting powertrain sizing approaches with low-level gearbox design methods. To this end, we first create analytical models of the individual transmission components: gears, shafts, bearings, clutches, and synchronizers. Second, we construct a transmission by systematically configuring a topology with these components. Third, we integrate the composed transmission within a powertrain and vehicle model, and compute the minimum-energy control strategies and design, employing two solution algorithms, namely dynamic programming and exhaustive search, respectively, providing global optimality guarantees. Finally, we carry out the design and control optimization of a one- and two-speed transmission for a small electric family car, whereby we observe that a two-speed transmission can improve the energy consumption by 0.5% with respect to a one-speedtransmission, whilst also satisfying the gradeability and performance requirements.This paper introduces a framework to systematically optimize the control and design of an electric vehicle transmission, connecting powertrain sizing studies to detailed gearbox design methods. To this end, we first create analytical models of individual components: gears, shafts, bearings, clutches, and synchronizers. Second, we construct a transmission by systematically configuring a topology with these components. Third, we place the composed transmission within a powertrain and vehicle model, and compute the minimum-energy control and design, employing solving algorithms that provide global optimality guarantees. Finally, we carry out the control and design optimization of a fixed- and two-gear transmission for a compact family electric vehicle, whereby we observe that a two-gear transmission can improve the energy consumption by 0.8 %, while also achieving requirements on gradeability and performance. We validate our framework by recreating the transmission that is mounted in the benchmark test case vehicle and recomputing the energy consumption over the New European Driving Cycle, where we notice an error in energy consumption of 0.2 %, affirming that our methods are suitable for gear ratio selection in powertrain design optimization