Electric vehicle battery pack energy management design for virtual platform based scenario testing - Thambippillai, Manoharan Aaruththiran (2024)
Electric vehicles (EVs) are currently explored extensively by automotive manufacturers to reduce global carbon emissions. However, consumer adoption is hindered by concerns over high costs, mileage, and insufficient infrastructures in many countries. EV battery pack state monitoring methods, in particular Artificial Neural Network (ANN) based State of Charge (SOC) estimators is widely explored. Despite achieving high estimation accuracy, current designs are computationally demanding. Moreover, there is also lack of research on effective battery pack SOC estimation techniques. This requires further investigation, since EVs use large battery packs to meet their mileage and voltage needs. For testing the EV components, the sole use of physical prototypes is expensive and might be time consuming to solve the issues identified.