Fuzzy Logic vs Equivalent Consumption Minimization Strategy for Energy Management in P2 Hybrid Electric Vehicles

2020 ◽  
Author(s):  
Hadi Rahmeh ◽  
Angelo Bonfitto ◽  
Sanjarbek Ruzimov
Keyword(s):  
Fuzzy Logic ◽  
Energy Management ◽  
Electric Vehicles ◽  
Hybrid Electric Vehicle ◽  
Hybrid Electric Vehicles ◽  
Net Energy ◽  
Energy Converter ◽  
Driving Cycles ◽  
Hybrid Electric ◽  
Equivalent Consumption Minimization Strategy

Abstract This paper presents a comparison between a Fuzzy Logic and an Equivalent Consumption Minimization Strategy for the energy management of a Hybrid Electric Vehicle in P2 configuration, i.e. with the secondary energy converter located downstream the clutch. The design of the two methods is conducted aiming to minimize the fuel consumption. Although the adopted strategies are not charge sustaining, an additional goal of the techniques is to obtain a net energy extracted from the battery over a driving cycle that is not far from zero. The presented simulation results are obtained in the case of two homologation driving cycles, namely NEDC and WLTP. The objective of the study is to demonstrate that a non-optimal rule-based method can achieve a performance that is equivalent to a model-based optimal analytical approach.

Adaptive Equivalent Consumption Minimization Strategy for Hybrid Electric Vehicles

2010 ◽  
Author(s):  
Simona Onori ◽  
Lorenzo Serrao ◽  
Giorgio Rizzoni
Keyword(s):  
Energy Management ◽  
Electric Vehicles ◽  
Hybrid Electric Vehicles ◽  
Optimal Solution ◽  
State Of Charge ◽  
Management Problem ◽  
Equivalence Factor ◽  
Hybrid Electric ◽  
Equivalent Consumption Minimization Strategy ◽  
Adaptation Law

This paper proposes a new method for solving the energy management problem for hybrid electric vehicles (HEVs) based on the equivalent consumption minimization strategy (ECMS). After discussing the main features of ECMS, an adaptation law of the equivalence factor used by ECMS is presented, which, using feedback of state of charge, ensures optimality of the strategy proposed. The performance of the A-ECMS is shown in simulation and compared to the optimal solution obtained with dynamic programming.

scholarly journals Fuzzy Logic-Based Duty Cycle Controller for the Energy Management System of Hybrid Electric Vehicles with Hybrid Energy Storage System

2021 ◽  
Vol 11 (7) ◽  
pp. 3192
Author(s):  
Muhammad Rafaqat Ishaque ◽  
Muhammad Adil Khan ◽  
Muhammad Moin Afzal ◽  
Abdul Wadood ◽  
Seung-Ryle Oh ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Energy Storage ◽  
Energy Management ◽  
Electric Vehicles ◽  
Management System ◽  
Power Flow ◽  
Hybrid Electric Vehicles ◽  
Pi Controller ◽  
Energy Management System ◽  
Hybrid Electric

Due to increasing fuel prices, the world is moving towards the use of hybrid electric vehicles (HEVs) because they are environmentally friendly, require less maintenance, and are a green technology. The energy management system (EMS) plays an important role in HEVs for the efficient storage of energy and control of the power flow mechanism. This paper deals with the design, modeling, and result-oriented approach for the development of EMS for HEVs using a fuzzy logic controller (FLC). Batteries and supercapacitors (SCs) are used as primary and secondary energy storage systems (ESSs), respectively. EMS consists of the ultra-power transfer algorithm (UPTA) and FLC techniques, which are used to control the power flow. The UPTA technique is used to charge the battery with the help of a single-ended primary inductor converter (SEPIC) during regenerative braking mode. The proposed research examines and compares the performance of FLC with a proportional integral (PI) controller by using MATLAB (Simulink) software. Three scenarios are built to confirm the efficiency of the proposed design. The simulation results show that the proposed design with FLC has a better response as its rise time (2.6 m) and settling time (1.47 µs) are superior to the PI controller.

scholarly journals Intelligent Control of Parallel Hybrid Electric Vehicles

1999 ◽  
Author(s):  
Bradley Glenn ◽  
Gregory Washington ◽  
Giorgio Rizzoni
Keyword(s):  
Fuzzy Logic ◽  
Electric Vehicles ◽  
Control Strategy ◽  
Hybrid Electric Vehicle ◽  
Fuzzy Logic Controller ◽  
Hybrid Electric Vehicles ◽  
Conventional Vehicle ◽  
Parallel Hybrid ◽  
Hybrid Electric ◽  
Reduce Emissions

Abstract Currently Hybrid Electric Vehicles (HEV) are being considered as an alternative to conventional automobiles in order to improve efficiency and reduce emissions. To demonstrate the potential of an advanced control strategy for HEV’s, a fuzzy logic control strategy has been developed and implemented in simulation in the National Renewable Energy Laboratory’s simulator Advisor (version 2.0.2). The Fuzzy Logic Controller (FLC) utilizes the electric motor in a parallel hybrid electric vehicle (HEV) to force the ICE (66KW Volkswagen TDI) to operate at or near its peak point of efficiency or at or near its best fuel economy. Results with advisor show that the vehicle with the Fuzzy Logic Controller can achieve (56) mpg in the city, while maintaining a state of charge of .68 for the battery pack, compared to (43) mpg for a conventional vehicle. This scheme has also brought to light various rules of thumb for the design and operation of HEV’s.

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