A rule-based energy management scheme for uninterrupted electric vehicles charging at constant price using photovoltaic-grid system

2018 ◽  
Vol 125 ◽  
pp. 384-400 ◽  
Author(s):  
Abdul Rauf Bhatti ◽  
Zainal Salam
Keyword(s):  
Energy Management ◽  
Electric Vehicles ◽  
Grid System ◽  
Rule Based ◽  
Management Scheme

Rule-Based Enhanced Energy Management Scheme for Electric Vehicles Fast-Charging Workplace Using Battery Stacks and Solar Power

2020 ◽  
Author(s):  
Zeeshan Ahmad Arfeen ◽  
Md Pauzi Abdullah ◽  
Usman Ullah Sheikh ◽  
Aliyu Hamza Sule ◽  
Hasan Thaer Alqaraghuli ◽  
...  
Keyword(s):  
Energy Management ◽  
Electric Vehicles ◽  
Solar Power ◽  
Rule Based ◽  
Management Scheme ◽  
Fast Charging

scholarly journals Analyzing the Improvements of Energy Management Systems for Hybrid Electric Vehicles Using a Systematic Literature Review: How Far Are These Controls from Rule-Based Controls Used in Commercial Vehicles?

2020 ◽  
Vol 10 (23) ◽  
pp. 8744
Author(s):  
Juan P. Torreglosa ◽  
Pablo Garcia-Triviño ◽  
David Vera ◽  
Diego A. López-García
Keyword(s):  
Literature Review ◽  
Energy Management ◽  
Electric Vehicles ◽  
Systematic Literature Review ◽  
Power Flow ◽  
Hybrid Electric Vehicles ◽  
Management Systems ◽  
Rule Based ◽  
Energy Management Systems ◽  
Hybrid Electric

The hybridization of vehicles is a viable step toward overcoming the challenge of the reduction of emissions related to road transport all over the world. To take advantage of the emission reduction potential of hybrid electric vehicles (HEVs), the appropriate design of their energy management systems (EMSs) to control the power flow between the engine and the battery is essential. This work presents a systematic literature review (SLR) of the more recent works that developed EMSs for HEVs. The review is carried out subject to the following idea: although the development of novel EMSs that seek the optimum performance of HEVs is booming, in the real world, HEVs continue to rely on well-known rule-based (RB) strategies. The contribution of this work is to present a quantitative comparison of the works selected. Since several studies do not provide results of their models against commercial RB strategies, it is proposed, as another contribution, to complete their results using simulations. From these results, it is concluded that the improvement of the analyzed EMSs ranges roughly between 5% and 10% with regard to commercial RB EMSs; in comparison to the optimum, the analyzed EMSs are nearer to the optimum than commercial RB EMSs.

A multi-level energy management system for multi-source electric vehicles – An integrated rule-based meta-heuristic approach

2013 ◽  
Vol 105 ◽  
pp. 304-318 ◽  
Author(s):  
João P. Trovão ◽  
Paulo G. Pereirinha ◽  
Humberto M. Jorge ◽  
Carlos Henggeler Antunes
Keyword(s):  
Energy Management ◽  
Electric Vehicles ◽  
Management System ◽  
Heuristic Approach ◽  
Energy Management System ◽  
Level Energy ◽  
Rule Based ◽  
Multi Level

Optimal Control based Calibration of Rule-Based Energy Management for Parallel Hybrid Electric Vehicles

2015 ◽  
Vol 4 (1) ◽  
pp. 178-189 ◽  
Author(s):  
Daniel Goerke ◽  
Michael Bargende ◽  
Uwe Keller ◽  
Norbert Ruzicka ◽  
Stefan Schmiedler
Keyword(s):  
Optimal Control ◽  
Energy Management ◽  
Electric Vehicles ◽  
Hybrid Electric Vehicles ◽  
Rule Based ◽  
Parallel Hybrid ◽  
Hybrid Electric

scholarly journals Novel Fuzzy Control Energy Management Strategy for Fuel Cell Hybrid Electric Vehicles Considering State of Health

Energies ◽  
2021 ◽  
Vol 14 (20) ◽  
pp. 6481
Author(s):  
Xiao Hu ◽  
Shikun Liu ◽  
Ke Song ◽  
Yuan Gao ◽  
Tong Zhang
Keyword(s):  
Genetic Algorithm ◽  
Fuel Cell ◽  
Fuzzy Control ◽  
Energy Management ◽  
Electric Vehicles ◽  
Cell Hybrid ◽  
Hybrid Electric Vehicles ◽  
Fuzzy Controller ◽  
Rule Based ◽  
Hydrogen Consumption

Due to the low efficiency and high pollution of conventional internal combustion engine vehicles, the fuel cell hybrid electric vehicles are expected to play a key role in the future of clean energy transportation attributed to the long driving range, short hydrogen refueling time and environmental advantages. The development of energy management strategies has an important impact on the economy and durability, but most strategies ignore the aging of fuel cells and the corresponding impact on hydrogen consumption. In this paper, a rule-based fuzzy control strategy is proposed based on the constructed data-driven online estimation model of fuel cell health. Then, a genetic algorithm is used to optimize this fuzzy controller, where the objective function is designed to consider both the economy and durability by combining the hydrogen consumption cost and the degradation cost characterized by the fuel cell health status. Considering that the rule-based strategy is more sensitive to operating conditions, this paper uses an artificial neural network for predictive control. The results are compared with those obtained from the genetic algorithm optimized fuzzy controller and are found to be very similar, where the prediction accuracy is assessed using MAPE, RMSE and 10-fold cross-validation. Experiments show that the developed strategy has a good generalization capability for variable driving cycles.

scholarly journals A Rule Based Energy Management System of Experimental Battery/Supercapacitor Hybrid Energy Storage System for Electric Vehicles

2016 ◽  
Vol 2016 ◽  
pp. 1-17 ◽  
Author(s):  
Qiao Zhang ◽  
Weiwen Deng ◽  
Sumin Zhang ◽  
Jian Wu
Keyword(s):  
Energy Management ◽  
Electric Vehicles ◽  
Management System ◽  
Storage System ◽  
Energy Storage System ◽  
Energy Management System ◽  
Rule Based ◽  
Hybrid Energy ◽  
Hybrid Energy Storage ◽  
Hybrid Energy Storage System

In this paper, a simple and efficient rule based energy management system for battery and supercapacitor hybrid energy storage system (HESS) used in electric vehicles is presented. The objective of the proposed energy management system is to focus on exploiting the supercapacitor characteristics and on increasing the battery lifetime and system efficiency. The role of the energy management system is to yield battery reference current, which is subsequently used by the controller of the DC/DC converter. First, a current controller is designed to realize load current distribution between battery and supercapacitor. Then a voltage controller is designed to ensure the supercapacitor SOC to fluctuate within a preset reasonable variation range. Finally, a commercial experimental platform is developed to verify the proposed control strategy. In addition, the energy efficiency and the cost analysis of the hybrid system are carried out based on the experimental results to explore the most cost-effective tradeoff.

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