Control Design of Fractional Multivariable Grey Model-Based Fast Terminal Attractor for High Efficiency Pure Sine Wave Inverters in Electric Vehicles
In this paper, a fast and efficient control method is proposed for a pure sine wave inverter used in an electric vehicle system, which can provide better performance under transient and steady-state conditions. The proposed control technique consists of a fast terminal attractor (FTA) and a fraction...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2024-12-01
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| Series: | World Electric Vehicle Journal |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2032-6653/15/12/556 |
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| Summary: | In this paper, a fast and efficient control method is proposed for a pure sine wave inverter used in an electric vehicle system, which can provide better performance under transient and steady-state conditions. The proposed control technique consists of a fast terminal attractor (FTA) and a fractional multivariable grey model (FMGM). The FTA with finite time convergence offers a faster convergence rate of the system state and a singularity-free solution. However, if the uncertain system boundaries are overestimated or underestimated, chatter/steady-state errors can occur during the FTA, which can lead to significant harmonic distortion at the output of the pure sine wave inverter. A computationally efficient FMGM is incorporated into the FTA to solve the chatter/steady-state error problem when an uncertain estimate of the system boundary cannot be satisfied. Simulation results show that the proposed control technique exhibits low total harmonic distortion. Experimental results of a prototype pure sine wave inverter are presented to support the results of the simulation and mathematical analysis. Since the proposed pure sine wave inverter outperforms the classical TA (terminal attractor)-controlled pure sine wave inverter in terms of convergence speed, computational efficiency, and harmonic distortion elimination, this paper will serve as a useful reference for electric vehicle systems. |
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| ISSN: | 2032-6653 |