Hardware in the Loop Model Development for Back to Back Testing in Battery Electric Vehicle

Abstract

This master thesis addresses the growing need for advanced testing methods in developing Battery Electric Vehicle (BEV) control units, particularly for software validation. As software validation becomes increasingly complex, relying solely on roller test benches demands significant resources and time. The primary aim of this research is to develop and enhance a Hardware-in-The-Loop (HiL) environment model for Back-to-Back (B2B) tests, specifically for a compact Sports Activity Vehicle (SAV). The objective of this thesis is to enhance the realism of simulations using the HiL toolset, allowing them to partially replicate the functions of a real vehicle. By simulating vehicle behavior, the B2B testing concept serves as a method for software validation. This approach involves testing the Electronic Control Unit (ECU) within the HiL environment under specific scenarios. Followed by analyzing and comparing the results with those from a roller test bench. The aim is to ensure that the results align within a certain threshold, indicating that software changes do not affect the outcomes. To achieve this, the thesis explores the theoretical foundations of electric drive systems and analyzes model behavior before and after implementing the proposed improvements. The thesis places a strong emphasis on B2B testing, which plays a crucial role as a method of comparing different software versions during BEV development. This focus is particularly important for power consumption, a critical aspect in the pursuit of energy efficiency in BEVs. The thesis employs several methods to enhance the HiL model, including refining electric motor parameters and introducing key functions such as brake recuperation and creep. In parallel, the battery model undergoes separate improvements to achieve greater accuracy. The results indicate significant improvements in HiL model functionality, such as better energy consumption accuracy, high reproducibility, and precise representation of vehicle dynamics and performance. These advancements are essential for ensuring that HiL models can reliably replicate real-world conditions in B2B tests. The improvements are evident when comparing the old and new HiL models against roller test bench data results. In summary, this master’s thesis makes a valuable contribution to the advancement of software validation techniques within the automotive industry. Improving the HiL model, offers a cost-effective approach to BEV control unit testing, paving the way for more efficient development processes and setting the stage for further research in this critical area.

Datum der Bewilligung	2024
Originalsprache	Englisch
Betreuer/-in	Christian Ertl (Betreuer*in)