Date of Completion
12-16-2015
Embargo Period
12-15-2015
Advisors
Cao Yang, Ali M. Bazzi
Field of Study
Electrical Engineering
Degree
Master of Science
Open Access
Open Access
Abstract
This thesis proposes the adaptive PI gain control to regulate sinusoidal ripple current (SRC) in battery charger systems. The SRC charge method is suited for fast and efficient charging. Y.D Lee (2015) propose that SRC charge method can reduce the charging time, decrease the charging temperature and improve the charging efficiency by applying optimal frequency to charge the battery. In order to determine optimal frequency for charging, the swept frequency is required in SRC charge method. Therefore, in order to perform SRC charge approach, the battery charger systems have to be capable of handling swept frequency input and regulating high frequency ripple current. However, the conventional designed charger would not be able to satisfy the aforementioned requirements because the control bandwidth of a fixed PI control gains is not designed for SRC but for a constant current profile. Therefore, the fixed PI gain control is limited to regulate the wide range frequency of ripple current.
The solution to the aforementioned issue is to apply the adaptive PI gain control based on Model Reference Adaptive Control (MRAC) so that it can regulate variable frequency of charging ripple current. The proposed approach shows that MRAC is the suitable solution for SRC charging because it is easily equipped into the conventional PI controller of a digital signal processor without any adjustments to the hardware design. As a result, there is no attenuation and phase delay under variable ripple frequencies condition (1~600 Hz). The performance of current control is compared with conventional fixed PI gain and the proposed adaptive variable gain. The proposed method is verified with simulation and experimental results.
Recommended Citation
Chen, Jen-Guey, "Adaptive PI Control to Realize Sinusoidal Ripple Current Charging in Battery Charger Systems" (2015). Master's Theses. 866.
https://digitalcommons.lib.uconn.edu/gs_theses/866
Major Advisor
Sung-Yeul, Park