Third order Model and Identification of Lead Acid Batteries Using Meta-Heuristic Algorithms and Experimental Measurements
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J. Loukil
Abstract
Today, lead acid batteries are even studied in an intensive way thanks to their economic interest related to their use in renewable energies and automotive sectors. The modelling of lead acid batteries can be done in several ways depending on the accuracy and system requirements. An accurate electrical model is very helpful for simulation, modelling, optimization, and control of battery cell systems. In this paper, an effective and suitable mathematical model of a battery cell has been treated. The implementation of the third order model well describes the internal aspect of the battery and reveals a good compromise between the precision and the complexity. In order to imitate the real behaviour for this kind of batteries and then to extract the charge and the discharge characteristics, an identification algorithm of internal parameters of the proposed model has been suggested with several methods: (i) the identification using electrical characteristics established by the manufacturer datasheet, (ii) the identification through a genetic algorithm and (iii) the identification using a particle swarm optimization. Using Matlab-Simulink, recovered simulations have been compared to those provided by POWER KINGDOM 7Ah-12V battery’s datasheet. Then, the behaviour of the third order model has been validated by an experimental test under real conditions. The setup is based on voltage and current sensors. An Arduino Board is used to acquire data from sensors and send them to the computer. The influence and variation effects of the temperature and the discharge current have been evaluated for the proposed model. Obtained results show an acceptable correspondence with the data issued by the manufacturer, the genetic algorithm, the particule swarm optimisation and the experimental work. These methods become an useful tool for researchers to determine easily the optimal internal parameters of lead acid batteries.
Abstract
Today, lead acid batteries are even studied in an intensive way thanks to their economic interest related to their use in renewable energies and automotive sectors. The modelling of lead acid batteries can be done in several ways depending on the accuracy and system requirements. An accurate electrical model is very helpful for simulation, modelling, optimization, and control of battery cell systems. In this paper, an effective and suitable mathematical model of a battery cell has been treated. The implementation of the third order model well describes the internal aspect of the battery and reveals a good compromise between the precision and the complexity. In order to imitate the real behaviour for this kind of batteries and then to extract the charge and the discharge characteristics, an identification algorithm of internal parameters of the proposed model has been suggested with several methods: (i) the identification using electrical characteristics established by the manufacturer datasheet, (ii) the identification through a genetic algorithm and (iii) the identification using a particle swarm optimization. Using Matlab-Simulink, recovered simulations have been compared to those provided by POWER KINGDOM 7Ah-12V battery’s datasheet. Then, the behaviour of the third order model has been validated by an experimental test under real conditions. The setup is based on voltage and current sensors. An Arduino Board is used to acquire data from sensors and send them to the computer. The influence and variation effects of the temperature and the discharge current have been evaluated for the proposed model. Obtained results show an acceptable correspondence with the data issued by the manufacturer, the genetic algorithm, the particule swarm optimisation and the experimental work. These methods become an useful tool for researchers to determine easily the optimal internal parameters of lead acid batteries.
Kapitel in diesem Buch
- Frontmatter I
- Contents XI
- Multi-phase Current Source Cycloconverter Using Amplitude Modulation Technique 1
- Bifurcation Analysis in a Self-Oscillating Series Resonant Converter 15
- Optimal design targeting the environmental footprint reduction of an electrical railway subsystem 29
- Long - Term Energy Losses Analyses For Jordanian Power system (Commercial Losses) 49
- A Novel Dynamics Approximation method for Analysis and Design of DC Drive Systems 59
- Third order Model and Identification of Lead Acid Batteries Using Meta-Heuristic Algorithms and Experimental Measurements 73
- A short circuit fault estimation in PMSM: A comparative study of an adaptive observer and an unknown inputs observer 93
- DCC and DTC of Three-Level Inverter Fed Brushless DC Motor Drives with Torque Ripple Reduction 113
Kapitel in diesem Buch
- Frontmatter I
- Contents XI
- Multi-phase Current Source Cycloconverter Using Amplitude Modulation Technique 1
- Bifurcation Analysis in a Self-Oscillating Series Resonant Converter 15
- Optimal design targeting the environmental footprint reduction of an electrical railway subsystem 29
- Long - Term Energy Losses Analyses For Jordanian Power system (Commercial Losses) 49
- A Novel Dynamics Approximation method for Analysis and Design of DC Drive Systems 59
- Third order Model and Identification of Lead Acid Batteries Using Meta-Heuristic Algorithms and Experimental Measurements 73
- A short circuit fault estimation in PMSM: A comparative study of an adaptive observer and an unknown inputs observer 93
- DCC and DTC of Three-Level Inverter Fed Brushless DC Motor Drives with Torque Ripple Reduction 113
