This webinar, presented by Gamma Technologies’ own Sagar Kulkarni (Senior Engineer, Application Engineering | Thermal Management), investigates methods aimed at streamlining complex thermal management models of battery electric vehicles (BEVs). A high-fidelity model of a BEV is used, featuring detailed thermal representations of components and several cooling, chiller, and AC circuits. The focus is on reducing runtime while finding the right compromise with accuracy and predictivity.
From an initial high fidelity model that runs significantly slower than real-time, multiple guided approaches were applied to facilitate a robust reduced order modeling approach. First by transitioning from 3D to 1D thermal modeling for the motor and coolant plate and then simplifying flow systems; the runtime is reduced to faster than real-time. This fast-running model maintains accuracy while making it suitable for HiL testing.
Finally, by implementing a unique parallel threading approach and splitting the integrated model into parallel sub-models running on multiple cores, real-time execution on HiL systems is achieved. This approach enables efficient testing and validation of thermal management systems without compromising accuracy.
In conclusion, this study highlights the successful development of a fast-running model for complete vehicle thermal management. It simplifies complex models, accelerates runtime, and enables HiL testing, offering a cost-effective and accurate approach for xEV development.