Visible to the public Temperature-dependent demagnetization nonlinear Wiener model with neural network for PM synchronous machines in electric vehicle

TitleTemperature-dependent demagnetization nonlinear Wiener model with neural network for PM synchronous machines in electric vehicle
Publication TypeConference Paper
Year of Publication2016
AuthorsZhang, Q., Ma, Z., Li, G., Qian, Z., Guo, X.
Conference Name2016 19th International Conference on Electrical Machines and Systems (ICEMS)
Date Publishednov
ISBN Number978-4-88686-098-9
KeywordsBP Neural Network, coercive force, compensation, composability, compositionality, Data models, demagnetisation, Demagnetization, electric vehicle, electric vehicles, intrinsic coercivity, Magnetic flux, Magnetic Remanence, Mathematical model, motor temperature, neural nets, Neural Network, Nonlinear Wiener model, permanent magnet flux, permanent magnet motors, permanent magnet synchronous motor demagnetization, PM synchronous machine, PMSM, power engineering computing, pubcrawl, remanence, Resiliency, synchronous motors, temperature, temperature compensation, Temperature-dependent demagnetization nonlinear Wiener model
Abstract

The inevitable temperature raise leads to the demagnetization of permanent magnet synchronous motor (PMSM), that is undesirable in the application of electrical vehicle. This paper presents a nonlinear demagnetization model taking into account temperature with the Wiener structure and neural network characteristics. The remanence and intrinsic coercivity are chosen as intermediate variables, thus the relationship between motor temperature and maximal permanent magnet flux is described by the proposed neural Wiener model. Simulation and experimental results demonstrate the precision of temperature dependent demagnetization model. This work makes the basis of temperature compensation for the output torque from PMSM.

URLhttps://ieeexplore.ieee.org/document/7837533/
Citation Keyzhang_temperature-dependent_2016