Optimal Sizing and Improved Low-Pass Filter Energy Management for Hybrid Energy Storage Electric Vehicles

The global promotion of electric vehicle usage is a response to the challenges of energy crises and climate change. However, significant drawbacks remain, particularly related to the high costs and limitations of onboard energy storage. To mitigate these issues, the concept of Hybrid Energy Storage Systems, which integrate batteries with complementary energy storage solutions, has gained attention. This study focuses on the optimal sizing and energy management strategy of Hybrid Energy Storage Systems, which are critical for enhancing the performance and viability of these systems in electric vehicles. An Improved Low-Pass Filter is introduced to address limitations of conventional low-pass filters, including phase shift effects and state of charge limitations while optimizing the cut-off frequency and ensuring adaptability to varying driving conditions. Particle Swarm Optimization is employed to achieve optimal sizing of the Hybrid Energy Storage Systems and to develop an efficient energy management system. The performance of the Improved Low-Pass Filter is validated against a Fuzzy Logic Controller and a conventional low-pass filter across various driving cycles. Simulation results demonstrate that the proposed Improved Low-Pass Filter significantly enhances performance, achieving up to an 8.345 improvement in city driving conditions compared to battery-only electric vehicles. © 2013 IEEE.