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The sustainable mobility trend touches the racing world as well, from thehybridization of Formula 1 (F1) and Le Mans Hypercars to the fully electricFormula E racing class. In this scenario, the research community is studyinghow to push electric racing vehicles to their limit, combining vehicle dynamicsand energy management, to successfully solve the minimum lap time problem.Recently, this class of problems has been enlarged towards optimal sizing, witha particular interest in batteries, which represent the main bottleneck forelectric vehicle performance. In this work, starting from a thorough review ofliterature approaches, we define a general optimization framework of minimumlap and race time problems for electric vehicles, suitable to figure out theimpact of different modeling choices on both problem structure and optimalvariables profiles. Exploiting a case study on Generation 3 (Gen 3) of FormulaE cars, we delve into the impact of battery models' complexity on both optimalsizing and optimal battery usage. We show how highly detailed models arenecessary to study the evolution of both battery and vehicle control variablesduring the race, while, simple models are more than sufficient to address thebattery sizing problem.

Battery model impact on time-optimal co-design for electric racing cars: review and application