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All Journal International Journal of Power Electronics and Drive Systems (IJPEDS)
Vinh, Vo Quang
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Control & Systems Engineering Electrical & Electronics Engineering

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Machine learning-based lithium-ion battery life prediction for electric vehicle applications Ha, Vo Thanh; Vinh, Vo Quang; Truc, Le Ngoc
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 15, No 3: September 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v15.i3.pp1934-1941

Abstract

The actual and anticipated battlefield creates a model capable of accurately estimating the lifetime of lithium-ion batteries used in electric cars. This inquiry uses a technique known as supervised machine learning, more particularly linear regression. In lithium-ion batteries, modeling temperature-dependent per-cells is the basis for capacity calculation. When a sufficient quantity of test data is accessible, a linear regression learning method will be utilized to train this model, ensuring a positive outcome in forecasting battery capacity. The conclusions drawn in the article are derived from the attributes of the initial one hundred charging and discharging cycles of the battery, enabling the determination of its remaining power. This determination facilitates the swift identification of battery manufacturing procedures and empowers consumers to detect flawed batteries when signs of performance degradation and reduced longevity are observed. MATLAB simulations have demonstrated the accuracy of the projected results, exhibiting a margin of error of approximately 9.98%. With its capacity to provide a reliable and precise means of estimating battery lifespan, the developed model holds the potential to revolutionize the electric vehicle industry.
Advanced control structures for induction motors with ideal current loop response using field oriented control Ha, Vo Thanh; Lam, Nguyen Tung; Ha, Vo Thu; Vinh, Vo Quang
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 10, No 4: December 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1637.79 KB) | DOI: 10.11591/ijpeds.v10.i4.pp1758-1771

Abstract

Field oriented control (FOC) is widely used for high performance induction motor (IM) electrical drive systems. Typically, FOC uses linear controls and space vector modulation (SVM) to control the fundamental components of the stator voltages. This work shows that based on a fast and precise inner current loop response one may flexibly employ different advanced control methods, to achieve high performance outer loops (speed and flux control). In this paper, novel approaches based on dead-beat scheme for the current loop combining with exact linearization, backstepping controls, and fatness-based methods for the outer loop are proposed. By comparing with classical PI control, the proposed method shows the outstanding features of system response such as fast, accurate and decoupling properties. The performance evaluation is given by experimental results.
Co-Authors Ha, Vo Thanh Ha, Vo Thu Lam, Nguyen Tung Truc, Le Ngoc