Real-time range optimization for selected destinations by Dynamic Energy Management Strategy (DEMS) in BEV’s

The automotive industry has undergone significant transformation with the adoption of electric vehicles (EVs). However, to tackle range anxiety, the focus has shifted to energy management strategies for optimal range under different driving conditions. Developing an optimal energy management algorithm is crucial for overcoming optimal range and gaining a competitive edge in the market. This paper introduces a Dynamic Energy Management Strategy (DEMS) for electric vehicles (EVs), designed to optimize battery usage and extend driving range. Utilizing vehicle digital twin model, DEMS estimates energy consumption across Eco, Normal, and Sports driving modes by analyzing vehicle velocity profiles and pedal inputs. By calculating actual battery consumption and pinpointing excess power usage, DEMS operates in a closed loop to periodically assess the power gap based on real-time vehicle conditions, including HV components like the Electric Drive system, DCDC, E-compressor and E-Heater; and intelligently allocates energy to each component, ensuring optimal performance. DEMS automatically selects the best drive mode and strategically manages energy distribution, prioritizing essential functions such as the drivetrain, followed by comfort features like heating or air conditioning, and luxury features like ambient lighting or seat massagers. This dynamic energy allocation is continuously adjusted to maximize efficiency, making EVs more efficient and extending their range. Simulations demonstrate that this approach can extend battery life and driving range, offering a promising solution for commercial EVs with existing battery technology. This strategy advances the sustainability and functionality of battery electric vehicles in modern transportation ecosystems.