AI-Driven Solutions for Optimizing Autonomous Vehicle Battery Usage

Abstract

The automotive industry is introducing energy efficiency, and electric vehicles (EVs) and autonomous vehicles (AVs) have become pivotal for future mobility. AV owners and passengers can take full advantage of cutting-edge technology embedded in an electrified powertrain instead of worrying about adjusting the powertrain components to achieve maximum efficiency. For EVs, the vehicle's mission includes reaching the destination with a minimum possible energy cost and a large remaining battery capacity if an onboard battery charger is not installed. For autonomous EVs, the design includes two tasks: planning and operation. One of the skills under planning is to plan the energy-efficient AV future driving behavior. In this design, the planner can compute a specific acceleration and velocity set point such that the powertrain will achieve these targets by managing the battery system states based on the vehicle and road constraints. AVs can potentially divide decision-making into subsets, and battery management is one of them.