An adaptive cabin air recirculation strategy for an electric truck using a coupled CFD-thermoregulation approach

Abstract

Cabin climatization is one of the largest auxiliary loads in an electric vehicle, and its performance significantly affects the driving range. Recirculating climatized air from the cabin has been shown to reduce energy consumption, but at the risk of fogging the windows and deteriorating the air quality. Therefore, many automobile manufacturers refrain from adopting it at low ambient temperatures. In this paper, an adaptive recirculation strategy that takes these issues into account is proposed and studied on an electric truck cabin while heating. Numerical simulations were performed using a coupled CFD-thermoregulation model, with the consideration of humidity and CO 2 . The JOS-3 thermoregulation model was employed for estimations of skin temperatures and evaporation of vapor from the skin, and the Berkeley comfort model was used to evaluate the comfort metrics. Ten scenarios were considered at various vehicle speeds, temperatures, and relative humidity levels while evaluating them with and without the proposed return-air strategy. The controller adapted between humidity and CO 2 -critical conditions during run-time. The fresh-air mass flow requirements reduced with increasing difference between the setpoint and ambient vapor mass fractions under humidity critical conditions, and plateaued at 10 g/s where CO 2 was more critical. The proposed strategy provided energy savings ranging from 9% to 34% depending on the operating condition. • An adaptive return-air strategy for an electric vehicle cabin is developed. • CFD-thermoregulation models are used to evaluate cabin-passenger interactions. • A parameter for scenario independent return-air ratio (RAR) estimation is defined. • A good estimation of RAR can be obtained with the steady-state analytical solution. • The net energy savings increase linearly with the RAR employed up to 34%.

Topics & Concepts