Overview of Sensitivity Analysis Methods Capabilities for Traction AC Machines in Electrified Vehicles

Pedram Asef, Andrew Lapthorn

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)
26 Downloads (Pure)


A robust design in electrified powertrains substantially helps to enhance the vehicle's overall efficiency. Robustness analyses come with complexity and computational costs at the vehicle level. The use of sensitivity analysis (SA) methods in the design phase has gained popularity in recent years to improve the performance of road vehicles while optimizing the resources, reducing the costs, and shortening the development time. Designers have started to utilize the SA methods to explore: i) how the component and vehicle level design options affect the main outputs i.e. energy efficiency and energy consumption; ii) observing sub-dependent parameters, which might be influenced by the variation of the targeted controllable (i.e. magnet thickness) and uncontrollable (i.e. magnet temperature) variables, in nonlinear dynamic systems; and iii) evaluating the interactions, of both dependent, and sub-dependent controllable/uncontrollable variables, under transient conditions. Hence the aim of this study is to succinctly review recent utilization of SA methods in the design of AC electric machines (EM)s used in vehicle powertrains, to evaluate and discuss the findings presented in recent research papers while summarizing the current state of knowledge. By systematically reviewing the literature on applied SAs in electrified powertrains, we offer a bibliometric analysis of the trends of application-oriented SA studies in the last and next decades. Finally, a numerical-based case study on a third-generation TOYOTA Prius EM will be given, to verify the SA-related findings of this article, alongside future works recommendations.

Original languageEnglish
Pages (from-to)23454 - 23471
Number of pages18
JournalIEEE Access
Publication statusPublished - 3 Feb 2021


  • AC machines
  • Automotive engineering
  • electric vehicles
  • permanent magnet machines
  • robustness
  • sensitivity analysis
  • statistics
  • time series analysis


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