Fuzzy Based Battery Charge Controller in Matlab

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Fuzzy Based Battery Charge Controller in Matlab

MATLAB helps in understanding the battery charging and discharging by the use of fuzzy logic this process helps to understand how does the charging time and discharging time varies. MATLAB can turn into a great tool for engineers and students. This software also helps us to understand on varying the battery characterstics how does it behave in real time.

This helps engineers to better understand the battery characteristics so as to improve battery parameters. This video shows how to use fuzzy logic designer, how to import .Fis file to workspace, membership function of different input and output, how to use fuzzy controller matrix, study the behavior of battery different charging state, Fuzzy tool box command. This will greatly enhance the productivity of students, engineers, researchers etc.

Abstract:

Battery charging process is non-linear, time-varying with a considerable time delay so it is difficult to achieve the best energy management performance by using traditional control approaches. To achieve the optimal charging and discharging status of the battery, a fuzzy control strategy is developed. The membership function database of the fuzzy sets, the fuzzification of the input and output variables and the evaluation of the fuzzy rules are used to support the control strategy. The Fuzzy Logic Algorithm used in battery charging process improves the efficiency of battery charging process and enhances the battery life.

The paper presents a hybrid system comprising of photovoltaic (PV) and battery with fuzzy logic control (FLC) to meet the demands of isolated off grid DC loads. Perturb and Observe (P&O) method is used to achieve the maximum power point tracking (MPPT) by controlling the duty cycle of a dc–dc boost converter. Fuzzy logic controller regulates the power flow of the battery by means of a bidirectional buck-boost converter. The complete energy management system has been validated in MATLAB/SIMUINK with variable solar irradiation profile. The simulation results show that the system with fuzzy logic control prolongs the battery lifespan by reducing the battery peak current up to 0.22% and also significantly decreases the settling time and peak overshoot of the DC load voltage up to 16.23% and 14.62% as compared to the system with conventional PID control.

The battery serves as the back-up and long term energy storage element in the proposed hybrid system. It helps to compensate for the fluctuating PV power output by storing the excess power and also discharging during low PV power situations. Battery bank is driven by two quadrant bidirectional dc–dc converter. The FLC controller changes the duty ratio for the switches S2 and S3 of the bidirectional converter to switch and regulate the mode of operation from charging to discharging. In the simulations, battery discharging current is considered to be positive whereas battery charging current as negative.

A fuzzy logic controller is designed to control the charging and discharging process of 100 A h, 12 V lead acid battery. There are various charging methods used to charge lead-acid batteries such as constant current method, constant voltage method, pulse charge method, float charge method, two stage constant voltage charging etc. The concept adopted in the proposed design is to vary the charging and discharging battery current in order to stabilize the DC link voltage.

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