Abstract
Hybrid electric vehicles (HEVs) have proved a feasible option to reduce fuel consumption and emissions. Furthermore, energy management strategies (EMSs) play a pivotal role in the performance of HEVs. This paper presents a novel real-time EMS, namely fuzzy adaptive-equivalent consumption minimization strategy (Fuzzy A-ECMS), for a parallel HEV. The proposed EMS is formulated by combining the ECMS, which is derived from Pontryagin's minimum principle (PMP), with a fuzzy logic controller adjusting the equivalent factor (EF) based on the deviation between reference state of charge (SOC) and actual SOC for a better SOC trajectory. Improved fuel economy and SOC charge sustainability are the main control objectives. To test and verify the performance of the studied controller, comparative simulations of the Fuzzy A-ECMS and rule-based EMS, conventional SOC-based A-ECMS together with standard ECMS under different standard driving cycles and a real driving cycle are conducted via MATLAB/Simulink and AVL CRUISE. The simulation results show the feasibility and effectiveness of Fuzzy A-ECMS, yielding 0.46% to 5.91% reduction of fuel consumption and more stable SOC charge sustainability compared with the other three EMSs.
Highlights
The gradual decline in global crude oil sources and stringent emissions rules have caused the urgent demand for vehicles with better fuel economy along with less emissions [1]
EQUIVALENT CONSUMPTION MINIMIZATION STRATEGY This paper presents a Fuzzy A-equivalent consumption minimization strategy (ECMS) for real-time energy management, which is developed based on a local optimization control strategy, ECMS, an algorithm derived from Pontryagin’s minimum principle (PMP), aiming to minimize the instantaneous equivalent fuel consumption
SIMULATION VALIDATION AND RESULT ANALYSIS After establishing the physical model of the parallel Hybrid electric vehicles (HEVs) in AVL CRUISE software, the real-time energy management controller, Fuzzy adaptive ECMS (A-ECMS), which includes the basic ECMS module and a fuzzy logic controller to regulate the equivalent factor (EF) based on the state of charge (SOC) deviation, is formulated in MATLAB/Simulink, with the AVL CRUISE interface connecting it to the physical HEV model
Summary
The gradual decline in global crude oil sources and stringent emissions rules have caused the urgent demand for vehicles with better fuel economy along with less emissions [1]. Denis et al proposed a fuzzy logic-based blended energy management strategy fed with driving condition information and demonstrated the efficiency by simulations [9]. These strategies are developed based on the. The proposed Fuzzy A-ECMS is applied to a parallel HEV and is verified by the comparison with rule-based EMS, conventional SOC-based A-ECMS and standard ECMS under the driving cycle of the Worldwide Harmonized Light Vehicles Test Procedure (WLTC) and the New European Driving Cycle (NEDC) as well as a real driving cycle called Beihang Campus Shuttle Bus Driving Cycle (BCSBDC) with two different initial EF settings.
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