Power management control strategy for a stand-alone solar photovoltaic-fuel cell–battery hybrid system

Power management systems are one of the most important components in modern hybrid vehicles. They are needed to optimize the operation of the hybrid system components. In this paper, a model for a fuel cell/battery vehicle is developed using PSAT and then tested with four power management control strategies utilizing the driving cycle of Amman city, the capital of Jordan. The main components of the hybrid vehicle are a PEM fuel cell, battery, and a brushless dc motor. PEM fuel cells are popular due to their good start up, high power density, and low operating temperature. The role of the battery in a hybrid system is to boost the system power during start-up and transient events in addition to storing the energy recovered from the braking process. The developed hybrid vehicle model is designed and configured so that it matches the power, acceleration, and maximum speed of a midsized vehicle powered by an internal combustion engine. The proposed control strategies are the thermostat strategy, fuel cell optimized strategy, load following strategy and fuzzy logic strategy. All four control strategies are implemented in simulation utilizing PSAT. The simulation results indicate that the best performance in terms of fuel economy is achieved by the load following control strategy.

Download Full-text

Improvement of Energy Management Control Strategy of Fuel Cell Hybrid Electric Vehicles Based on Artificial Intelligence Techniques

Journal Européen des Systèmes Automatisés ◽

10.18280/jesa.520601 ◽

2019 ◽

Vol 52 (6) ◽

pp. 541-550 ◽

Cited By ~ 1

Author(s):

Said Belhadj ◽

Karim Belmokhtar ◽

Kaci Ghedamsi Kaci Ghedamsi

Keyword(s):

Artificial Intelligence ◽

Fuel Cell ◽

Energy Management ◽

Electric Vehicles ◽

Control Strategy ◽

Cell Hybrid ◽

Hybrid Electric Vehicles ◽

Management Control ◽

Artificial Intelligence Techniques ◽

Fuel Cell Hybrid

Download Full-text

Power Management Control Strategy for PV-Battery Standalone System

2020 IEEE 9th Power India International Conference (PIICON) ◽

10.1109/piicon49524.2020.9112970 ◽

2020 ◽

Author(s):

Deeksha Bhule ◽

Sachin Jain ◽

Subhojit Ghosh

Keyword(s):

Power Management ◽

Control Strategy ◽

Management Control

Download Full-text

Development of a power management unit for small portable direct borohydride fuel cell–NiMH battery hybrid system

International Journal of Hydrogen Energy ◽

10.1016/j.ijhydene.2012.09.137 ◽

2012 ◽

Vol 37 (24) ◽

pp. 19103-19110 ◽

Cited By ~ 8

Author(s):

Ayşe Elif Sanlı ◽

Göksel Günlü ◽

Aylin Aytaç ◽

Mahmut Mat

Keyword(s):

Fuel Cell ◽

Power Management ◽

Hybrid System ◽

Management Unit ◽

Direct Borohydride Fuel Cell ◽

Nimh Battery ◽

Power Management Unit

Download Full-text

Design and Optimization of the Power Management Strategy of an Electric Drive Tracked Vehicle

Mathematical Problems in Engineering ◽

10.1155/2016/6185743 ◽

2016 ◽

Vol 2016 ◽

pp. 1-13 ◽

Cited By ~ 2

Author(s):

Qunzhang Tu ◽

Xiaochen Zhang ◽

Ming Pan ◽

Chengming Jiang ◽

Jinhong Xue

Keyword(s):

Power Management ◽

Electric Drive ◽

Fuel Economy ◽

Control Strategy ◽

Fuzzy Controller ◽

Management Control ◽

Drive System ◽

Tracked Vehicles ◽

Hybrid Particle Swarm Optimization ◽

Electric Drive System

This article studies the power management control strategy of electric drive system and, in particular, improves the fuel economy for electric drive tracked vehicles. Combined with theoretical analysis and experimental data, real-time control oriented models of electric drive system are established. Taking into account the workloads of engine and the SOC (state of charge) of battery, a fuzzy logic based power management control strategy is proposed. In order to achieve a further improvement in fuel economic, a DEHPSO algorithm (differential evolution based hybrid particle swarm optimization) is adopted to optimize the membership functions of fuzzy controller. Finally, to verify the validity of control strategy, a HILS (hardware-in-the-loop simulation) platform is built based on dSPACE and related experiments are carried out. The results indicate that the proposed strategy obtained good effects on power management, which achieves high working efficiency and power output capacity. Optimized by DEHPSO algorithm, fuel consumption of the system is decreased by 4.88% and the fuel economy is obviously improved, which will offer an effective way to improve integrated performance of electric drive tracked vehicles.

Download Full-text