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Journal : J-Innovation

Implementasi Maximum Power Point Tracker Berbasis Fuzzy Logic Controller dengan Zeta Converter Afifuddin Rizqi; Sutedjo; Endro Wahjono
J-Innovation Vol. 10 No. 1 (2021): Jurnal J-Innovation
Publisher : Politeknik Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (715.102 KB) | DOI: 10.55600/jipa.v10i1.16

Abstract

Implementation of photovoltaics as a renewable energy source is growing rapidly. The cost of implementing photovoltaic is very high therefore it is necessary to control the optimization of the PV. The V-I aspect of solar cells is nonlinear, changing with the intensity of sunlight and the surface temperature of the photovoltaic, causing the output power of the photovoltaic to vary. This research will use the zeta converter as a DC chooper controlled by MPPT based on fuzzy logic controller. Software Power Simulation (PSIM) is used to simulate MPPT. The MPPT fuzzy logic controller will be compared with the MPPT human psychology optimization (HPO). The simulation results show that MPPT fuzzy gets the same accuracy as MPPT HPO and is better than the average accuracy without MPPT which is 99,98%. Then the speed in finding the maximum MPPT fuzzy point gets a better time tracking when compared to the MPPT HPO which is 0,0283 seconds. MPPT fuzzy is able to exceed the maximum power at varying sunlight intensity and temperature.
Sistem Baterai Cell Balancing Pasif Menggunakan Kontrol Logika Fuzzy Tipe Mamdani untuk Baterai Pack Lithium Moh Rifqi Faqih; Novie Ayub Windarko; Endro Wahjono
J-Innovation Vol. 10 No. 2 (2021): Jurnal J-Innovation
Publisher : Politeknik Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (486.215 KB) | DOI: 10.55600/jipa.v10i2.111

Abstract

Lithium-ion batteries have been widely used in energy storage for electric vehicle and hybrid vehicle applications. After several cycles of charging and discharging, there is one cell whose performance and capacity decreases, causing the performance and capacity of the battery pack to decrease so that it cannot work optimally. So it is necessary to design a cell voltage balancing system to minimize cell voltage imbalance in the charging process. Passive balancing is widely implemented because of its simplicity, reliability, and relatively low cost. The balancing process must be carried out as quickly as possible as the battery is charging, so a PWM ignition technique using mamdani fuzzy is needed to discharge an unbalanced battery cell. The result are compared with no balancing system, fixed balancing 50% duty cycle system, and sugeno fuzzy logic balancing system. From the simulation result, using mamdani fuzzy the final delta voltage value is 0.0344 volt, energy charged is 58.18 Wh and the final State of Charge is 74%. When compared with other balancing method, it shows that using mamdani fuzzy logic method is more optimal because the final of delta voltage value is very small and the battery capacity charged is larger than other method.