Latest revision as of 13:46, 16 February 2021

Abstract

Sensorless control of Electric Vehicle (EV) drives is considered to be an effective approach to improve system reliability and to reduce component costs. In this paper, relevant aspects relating to the sensorless operation of EVs are reported. As an initial contribution, a hybrid sensorless control algorithm is presented that is suitable for a variety of synchronous machines. The proposed method is simple to implement and its relatively low computational cost is a desirable feature for automotive microprocessors with limited computational capabilities. An experimental validation of the proposal is performed on a full-scale automotive grade platform housing a 51¿kW Permanent Magnet assisted Synchronous Reluctance Machine (PM-assisted SynRM). Due to the operational requirements of EVs, both the strategy presented in this paper and other hybrid sensorless control strategies rely on High Frequency Injection (HFI) techniques, to determine the rotor position at standstill and at low speeds. The introduction of additional high frequency perturbations increases the power losses, thereby reducing the overall efficiency of the drive. Hence, a second contribution of this work is a simulation platform for the characterization of power losses in both synchronous machines and a Voltage Source Inverters (VSI). Finally, as a third contribution and considering the central concerns of efficiency and autonomy in EV applications, the impact of power losses are analyzed. The operational requirements of High Frequency Injection (HFI) are experimentally obtained and, using state-of-the-art digital simulation, a detailed loss analysis is performed during real automotive driving cycles. Based on the results, practical considerations are presented in the conclusions relating to EV sensorless control.

Peer Reviewed

Document type: Article

Full document

The URL or file path given does not exist.

Original document

The different versions of the original document can be found in:

• http://hdl.handle.net/11556/555 under the license http://creativecommons.org/licenses/by-nc-nd/4.0/

• http://hdl.handle.net/2117/118056

• https://upcommons.upc.edu/bitstream/2117/118056/1/APEN%20for%20DRAC.pdf

• https://api.elsevier.com/content/article/PII:S0306261918307116?httpAccept=text/xml,

https://api.elsevier.com/content/article/PII:S0306261918307116?httpAccept=text/plain,

http://dx.doi.org/10.1016/j.apenergy.2018.05.019 under the license https://www.elsevier.com/tdm/userlicense/1.0/

• https://www.sciencedirect.com/science/article/pii/S0306261918307116,

https://ideas.repec.org/a/eee/appene/v224y2018icp647-658.html,

http://dsp.tecnalia.com/handle/11556/555,

https://upcommons.upc.edu/handle/2117/118056,

https://core.ac.uk/display/158802020,

https://academic.microsoft.com/#/detail/2802127459