Affiliation:
1. Loughborough University
2. Jaguar Land Rover
Abstract
<div class="section abstract"><div class="htmlview paragraph">The importance of designing and sizing a thermal management system for electric vehicle powertrains cannot be overstated. Traditional approaches often rely on model-based system design using supplier reference component data, which can inadvertently lead to undisclosed errors arising from the interactions between the components and the environment. This paper introduces a novel test facility for battery electric vehicle thermal management technology, which has been designed for neural network virtual sensor and non-linear multi-in multi-out control development. The paper demonstrates how a digital twin of the test bench can used to support the development of such technology. Additionally, this paper presents preliminary results from the test bench revealing insights into the performance and interactions of key components. For instance, there is an observed 30% reduction in the maximum flow rate of the pump integrated into the test bench compared to the specified value. Furthermore, the interactions between the pump and valve resulted in a non-linear flow rate response which is essential knowledge prior to developing new multi-in multi-out control strategies.</div></div>