An Optimization Methodology to Pre Design an Electric Vehicle Powertrain

Caillard, Pierre; Gillon, F.; Hecquet, Michel; Randi, Sid-Ali; Janiaud, Noëlle

doi:10.1109/vppc.2014.7007015

Cited by 17 publications

(1 citation statement)

References 12 publications

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“…This approach calculates the RP as the geometric mean of the points in the cluster and is implemented in [30][31][32][33][34][35][36]. The speed and the torque values of each point correspond to the geometrical dimensions of the point (i.e., the x and y coordinates of the point, respectively).…”

Section: ) Geometric Mean Rpmentioning

confidence: 99%

Drive Cycle-Based Design With the Aid of Data Mining Methods: A Review on Clustering Techniques of Electric Vehicle Motor Design With a Case Study

Abdel-Wahed,

Ullah,

Abdel-Khalik

et al. 2023

IEEE Access

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The electrification of the automotive has recently shaped the current revolution in transportation. Many automotive companies are now producing their own electric vehicle (EV) models. To cope with these advances, the various subsystems need to be improved regularly, and their issues need to be solved. A way to achieve this is to make use of the extensive amount of information available today. These data can give a better picture and propose ways for enhancements and solutions to problems. The huge amounts of data are dealt with using data mining techniques. This paper surveys the clustering technique, one of the data mining techniques, used in designing and optimizing the electrical machines used for EVs. It presents the various clustering methods used to classify the different operating points of the torque speed curve and summarizes them into just a few points to be considered in the optimization process. It then illustrates a case study, developing a general design process with the aid of various clustering techniques and comparing their performance. The case study is applied to a six-phase surface-mounted permanent magnet (SPM) synchronous machine used for an electric vehicle's propulsion and integrated onboard battery charger (IOBC) system. It suggests clustering techniques as an efficient means to achieve an optimal motor design over the entire driving cycle while considering only a few operating points to reduce time consumption and computational burdens, while getting acceptable results.

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