Computational Range Maximization Under Current Constraints for Heavy-Duty Electric Vehicles

In this article, we study model-based Heavy-Duty Electric Vehicle (HDEV) range maximization under bounds for the discharge current, as imposed by the onboard Battery Management System (BMS). We present a computational optimization framework that facilitates design of optimal controls for battery Equivalent Circuit Models (ECM) of different fidelities. The objective is to compare the different model predictions and assess the efficacy of simple control laws relative to more complex ones that attempt to exploit the battery's modeled characteristics. We confine our attention to windless flat-track conditions to isolate the effect of the Battery Energy System (BES). In numerical simulations, we focus on Lithium-Titanate Oxide (LTO) batteries, which have been found prime candidates for HDEV applications. The results show that the maximum range predictions, and the associated optimal control policies, depend substantially on the ECM utilized. However, for all models, good maximal range predictions are also obtained by using simple constant controls. This is consistent with Keller's theory of optimal pacing.