Comparative Analysis of Rule-Based Energy Management Strategies for Hybrid Energy Storage Electric Vehicles

Maghfiroh, Hari and Wahyunggoro, Oyas and Cahyadi, Adha Imam (2025) Comparative Analysis of Rule-Based Energy Management Strategies for Hybrid Energy Storage Electric Vehicles. Comparative Analysis of Rule-Based Energy Management Strategies for Hybrid Energy Storage Electric Vehicles.

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Abstract

Effective Energy Management Strategies (EMS) are crucial for optimizing power distribution in Hybrid Energy Storage Systems (HESS), enhancing battery longevity, and improving efficiency in Electric Vehicles (EVs) and Automated Guided Vehicles (AGVs) since EVs and AGVs share similar electric propulsion systems. This study evaluates two rule-based EMS approaches, Low-Pass Filter (LPF) and Fuzzy Logic Controller (FLC), through simulations using the Worldwide Harmonized Light Vehicles Test Cycle (WLTC) and a real drive cycle (RDC). In RDC, LPF EMS extends battery life by 34.94 and increases total travel distance by 25.81 , while FLC EMS improves battery life by 23.08 and total distance by 19.30. LPF EMS enhances efficiency by smoothing transient loads, while FLC EMS better adapts to dynamic conditions by utilizing the supercapacitor. These findings indicate that LPF EMS is ideal for battery longevity, whereas FLC EMS suits applications with variable loads. Given their shared energy challenges, these insights benefit both EV and AGV systems, advancing efficient electric mobility. © 2025 IEEE.

Item Type: Article
Additional Information: Cited by: 1
Uncontrolled Keywords: Automatic guided vehicles; Battery management systems; Charging (batteries); Electric power distribution; Electric propulsion; Energy efficiency; Energy management systems; Energy storage; Hybrid power; Hybrid vehicles; Industrial electronics; Secondary batteries; Storage management; Automated guided vehicles; Controller energy; Drive cycles; Energy; Fuzzy logic controllers; Hybrid energy storage; Low-pass filters; Management strategies; Propulsion system; Rule based; Fuzzy logic
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: Faculty of Engineering > Electrical and Information Technology Department
Depositing User: Rita Yulianti Yulianti
Date Deposited: 09 Jan 2026 01:19
Last Modified: 09 Jan 2026 01:19
URI: https://ir.lib.ugm.ac.id/id/eprint/24910

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