Pla, Benjamín (Universitat Politècnica de València), Bares, Pau (Universitat Politècnica de València), Aronis, André (Universitat Politècnica de València), Tomanik, Victor (Universitat Politècnica de València)

Battery Temperature Control by Dynamic Programming with Power Demand Prediction

Scheduled for presentation during the Regular session "Energy Management" (FrB2), Friday, November 1, 2024, 11:10−11:30, Room T2

7th IFAC Conference on Engine and Powertrain Control, Simulation and Modeling, Oct 30 - Nov 1, 2024, Dalian, China

This information is tentative and subject to change. Compiled on January 2, 2025

Abstract

Battery Electric Vehicles (BEV) commonly dispose from route scheduling algorithms to assess the driver with future prediction of the state of charge (SOC) to cope with range limitations. In addition, these vehicles use an important part of the battery energy in controlling the temperature of the battery ensuring an average battery temperature between 20 to 35 ºC for safety and efficient operation. The work presented in this paper analyses the use of dynamic programming and physically derived thermal models of the coolant and the battery temperature evolution to optimize the energy delivered to the coolant flow. Experimental tests have been performed in a battery pack refrigerated by a cold plate to demonstrate the capabilities of the proposed methodology.