Automotive Engineering
NOTICE OF SEMINAR PRESENTATION
CANDIDATE: Dante Zollo
DEGREE SOUGHT: MASc
DATE: 8/1/2025
TIME: 11:30am
PLACE: Room 1102
TITLE: Automated Calibration Algorithm Applied To Electric Vehicle Heat Generation Logic Control Using Brent's Minimization Method
Abstract
This work proposes an automated calibration method for control algorithms, based on look-up tables. The method has been applied to the algorithm strategy for battery heating controlling the thermal energy generated by the electrified powertrain. Look-Up tables are widely used in powertrain control systems, both for electric powertrains and for internal combustion engine powertrains, as they enable real-time computations based on precomputed results. This makes them ideal for online applications due to their low computational cost. The main issue of using look-up tables comes from their calibration. At present, this calibration requires expert engineers that have to tune these tables through a highly time consuming and resource intensive process which involves extensive testing and iterations. Furthermore, this manual process usually leads to suboptimal performances . This work proposes an algorithm capable of automating the calibration process through optimization, making it less human-dependable and enhancing the final performance of the tuned table. The algorithm automatically selects all the possible combinations of table entrees optimizing, in this way, each bin of the table at a time. A comparison between two optimization techniques, Golden Section Search and Brent’s Minimization Method, will be carried out showing eventually which are the advantages of the proposed method. The results confirmed that Brent's Minimization Method has a faster convergence than Goden Section Search, thus it is able to calibrate the lookup table faster. Moreover, the result of the proposed method show a much higher accuracy compared to the original method used by the industrial partner.