Investigation of Critical Parameters for Selecting Energy-Optimal Cruising Speed Using a Low-Computation Framework

This article proposes a low-computation framework for on-board calculation of energy-optimal cruising speed, and uses the framework to investigate the critical parameters for energy-optimal cruising speed determination. The main features of the proposed framework are as follows: first, inclusion of all internal and external vehicle losses, particularly the accessory loads, which have a large impact on optimal cruising speed and have not been investigated in other works, second, use of accurate motorinverter loss look-up-tables rather than approximated polynomial models, and, third, no requirement for connected data or knowledge of the future route, as the optimal cruising speed is calculated precisely for the current state of the vehicle and surroundings. To validate the framework, three electric vehicle models are developed in MATLABSimulink and tuned to match real-world data for a Chevrolet Bolt, Chevrolet Spark, and Tesla Model S. Furthermore, an algorithm is developed to determine near-optimal speed transitions when the optimal cruising speed changes.