This conference paper was submitted for presentation at the NAFEMS World Congress 2025, held in Salzburg, Austria from May 19–22, 2025.

Abstract

Ensuring an acceptable vehicle range, good passenger thermal comfort, and the safety of electric components is a delicate trade-off in terms of system architecture, component sizing, and control logic definition. This paper presents a comprehensive study on the energy and thermal management of electric vehicles, utilizing a full-fidelity system model executed in Simcenter Amesim. The focus is on the integration of high-fidelity subsystem models, including the battery, cabin, and electric motor, within various drive cycles to identify and address real-world thermal management challenges, particularly those experienced in extreme environments. Current issues include the prioritization of battery cooling over cabin climate control, leading to suboptimal passenger comfort. The paper explores the integration of 3D simulation results for enhanced fidelity. First, the objective is to leverage the accuracy of computational fluid dynamics (CFD) models of cabin thermal management. An innovative methodology to generate the Reduced Order Model is presented. It consists of a step-by-step process: importing the geometry and results from the existing CFD simulation files in Simcenter STAR-CCM+, choosing the desired spatial discretization by adding cutting planes, and then mapping all 3D CFD results onto the model. Secondly, an accurate model of the electric drive is generated to consider electromagnetic and thermal aspects. Starting from an electric machine model developed with Simcenter E-Machine Design, maps of performance and losses, as well as a Lumped Parameter Thermal Network (LPTN) model, are generated and exported. The system-level model benefits from an accurate performance/energy consumption model and a realistic temperature estimation of the main motor components during transient cycles. The full vehicle model is used on driving cycles in countries with extreme temperature conditions: 40°C and 2000 W/m² solar load in Saudi Arabia and -20°C and night conditions in Alaska. This integrated vehicle energy management/thermal management framework offers significant advancements in simulation accuracy while maintaining fast computation times (faster than real-time). This innovative workflow provides valuable insights into system performance under challenging conditions and enables more effective strategies in electric vehicles.