Addressing the challenges of Battery Management System development using an MBD framework
Streamline the development of BMS control algorithms to maximize range, battery life, and safety.
The process of engineering battery management system (BMS) control software is a complex activity that must produce a balance between immediate battery power performance and long duration safe operation. Robust algorithms are needed to accurately determine battery states to ensure reliable information on available energy and power levels and the life of the battery. Developing underlying algorithms directly on a hardware battery prototype is time-consuming, prone to errors, and introduces safety fail-points. The model-based design (MBD) framework provides a mechanism to reuse test scenarios at different stages of development and operating conditions to ensure the safe operation of the battery.
In this webinar, we’ll explain how to set up an MBD framework to develop and test the BMS algorithms on a virtual battery pack. It will highlight how advanced optimal control techniques enhance battery performance, how engineers can reuse the virtual battery pack during different development stages using different test environments (e.g., MIL, SIL, and HIL) and how to reuse test scenarios at different stages of development.
You will learn:
- Key subsystems within a Battery Management Control System that pertain to range anxiety, safety, and optimal vehicle performance
- How a virtual battery models be used to analyze control system behavior and to rapidly test its performance in a repeatable fashion, including thermal management strategies
- Key factors that affect the aging of the battery pack, and how can the BMS help to monitor and extend the life of the battery pack
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