Optimization of the Cabin Comfort Control of a Battery Electric Vehicle

13297

09/19/2022

Authors Abstract
Content

"This paper presents a joint research project between Ricardo and Jaguar Land Rover to study a number of updates to the control system for a battery electric vehicle to reduce the thermal energy required by the vehicle. These savings can be translated into increased vehicle range, robustness to ambient temperature variations or a reduce battery size. The paper starts with the application of model predictive control to optimise the cabin comfort control in a battery electric vehicle. The work is based on detailed comfort models of the cabin occupants simulated over a range of conditions to provide updated control setpoints to the comfort control algorithms. The control system is analysed offline using optimal control to establish the maximum potential from changes to the control system and to provide a framework for the control algorithm development. Following on from this study, a model predictive controller has been implemented that optimises the multivariable control of recirculation flaps, heater and blower control, whilst simultaneously respecting limits such as in-cabin CO2 concentrations. The paper considers how knowledge of the vehicle route can be used to further optimise the cabin comfort control whilst minimising energy consumption. All of these approaches have been successfully demonstrated in vehicle test results from a climatic wind tunnel. "

Meta TagsAdditional Details
Published
Sep 19, 2022
Product Code
13297
Content Type
Video