Sliding innovation filter to estimate power converters of electric vehicles

Mohammad AlShabi; Andrew Gadsden; Khaled Obaideen

doi:10.1117/12.2664057

15 June 2023 Sliding innovation filter to estimate power converters of electric vehicles

Mohammad AlShabi, Andrew Gadsden, Khaled Obaideen

Proceedings Volume 12513, Energy Harvesting and Storage: Materials, Devices, and Applications XIII; 1251308 (2023) https://doi.org/10.1117/12.2664057
Event: SPIE Defense + Commercial Sensing, 2023, Orlando, Florida, United States

Abstract

The sliding innovation filter (SIF) is a recently developed estimation technique that has gained widespread use. It is a predictor-corrector filter that utilizes a hyperplane and applies a force to allow estimates to fluctuate about it. SIF belongs to the same family as the smooth variable structure filter and sliding mode observer, and it is stable and robust in the face of uncertainties. This paper discusses the use of SIF for estimating the states of Power Converters, which play a crucial role in Electric Vehicles (EVs) by converting high-voltage DC from the battery to low-voltage AC used by the motor. One of the main challenges in Power Converters is accurately estimating their states, such as input voltage, output voltage, and inductor current, which are critical for optimal control and efficient operation. The SIF has demonstrated promising results in addressing this challenge.

Conference Presentation

Citation Download Citation

Mohammad AlShabi, Andrew Gadsden, and Khaled Obaideen "Sliding innovation filter to estimate power converters of electric vehicles", Proc. SPIE 12513, Energy Harvesting and Storage: Materials, Devices, and Applications XIII, 1251308 (15 June 2023); https://doi.org/10.1117/12.2664057

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