2 research outputs found

    A Lumped Parameter Thermal Model for Single Sided AFPM Machines with Experimental Validation

    Get PDF

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

    Get PDF
    © 2021 The Author(s). This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/.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.Peer reviewe
    corecore