Characterization of the parameters of interior permanent magnet synchronous motors for a loss model algorithm

Caruso, M.; Tommaso, A. O. Di; Miceli, R.; Nevoloso, C.; Spataro, C.; Viola, Fabio

doi:10.1016/j.measurement.2017.04.039

Cited by 39 publications

(11 citation statements)

References 25 publications

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“…Therefore, only iron consumption and copper consumption are considered in this paper. The loss model of permanent magnet synchronous motor can be referred to [44,45].…”

Section: Numerical Simulation and Loss Model Of Dual Motormentioning

confidence: 99%

Energy Recovery Strategy Numerical Simulation for Dual Axle Drive Pure Electric Vehicle Based on Motor Loss Model and Big Data Calculation

2018

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Aiming at the braking energy feedback control in the optimal energy recovery of the two-motor dual-axis drive electric vehicle (EV), the efficiency numerical simulation model based on the permanent magnet synchronous motor loss was established. At the same time, under different speed and braking conditions, based on maximum recovery efficiency and data calculation of motor system, the optimization motor braking torque distribution model was established. Thus, the distribution rule of the power optimization for the front and rear electric mechanism was obtained. This paper takes the Economic Commission of Europe (ECE) braking safety regulation as the constraint condition, and finally, a new regenerative braking torque distribution strategy numerical simulation was developed. The simulation model of Simulink and CarSim was established based on the simulation object. The numerical simulation results show that under the proposed strategy, the average utilization efficiency of the motor system is increased by 3.24% compared with the I based braking force distribution strategy. Moreover, it is 9.95% higher than the maximum braking energy recovery strategy of the front axle. Finally, through the driving behavior of the driver obtained from the big data platform, we analyze how the automobile braking force matches with the driver’s driving behavior. It also analyzes how the automobile braking force matches the energy recovery efficiency. The research results in this paper provide a reference for the future calculation of braking force feedback control system based on big data of new energy vehicles. It also provides a reference for the modeling of brake feedback control system.

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“…Therefore, only iron consumption and copper consumption are considered in this paper. The loss model of permanent magnet synchronous motor can be referred to [44,45].…”

Section: Numerical Simulation and Loss Model Of Dual Motormentioning

confidence: 99%

Energy Recovery Strategy Numerical Simulation for Dual Axle Drive Pure Electric Vehicle Based on Motor Loss Model and Big Data Calculation

2018

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“…The latter formula shows the motor input power as follows:

\begin{matrix} right leftthickmathspace.5em \\ P_{1} & = \sqrt{3} U I \cos φ = P_{2} + P_{normalFe} + P_{m} + P_{normalCu} \\ = P_{normalsF} + P_{normalrF} + P_{m} + P_{normalCu} \\ = k_{1} T^{2} + k_{2} T + k_{3} + k_{4} I^{2} + k_{5} + m I^{2} R_{normalCu} \end{matrix}

In order to enlarge the individuality of the simplest monitoring model of motor [9], a self‐learning method of parameter identification based on multi‐population genetic algorithm (MPGA) is established. MPGA is not easy to fall into local optimal, and it greatly improves the robustness and global search ability of the algorithm [10] (see Fig. 4).…”

Section: System Of the Secondary Balancementioning

confidence: 99%

Energy‐saving system of secondary balance for the hybrid power of the pumping unit

Chen

Wang

et al. 2018

J. eng.

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“…Another type of PMSG is the interior permanent magnet synchronous generator (IPMSG); it is a salient pole synchronous generator with a cylindrical rotor which has permanent magnet embedded inside the rotor body. These embedded permanent magnet generator cause saliency in terms of direct axis and quadrature axis reactance (Caruso et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

Assessment of proposed maximum power point tracking–unity power factor algorithms for optimum operation permanent magnet synchronous generator–based wind turbine

2020

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It is very important to select proper maximum power point tracking algorithm in order to achieve best performance and low cost for wind turbine–generator combination. A permanent magnet synchronous generator steady-state unity power factor analytical model based on a current source—equivalent circuit is provided. Validation of the identified load angle effect in current source as compared with that of the commonly used voltage source permanent magnet synchronous generator is presented. Then three new maximum power point tracking–load angle control algorithms based on current source model are presented. They all apply magnitude and frequency control techniques for Digital Signal Processor control systems. The first one presents maximum power point tracking–unity power factor applying constrained load angle control algorithm. The merits of the next two developed schemes are quickly and precisely tracking the maximum power output of the wind turbine; thus, the second and third algorithms are then characterized with linear control systems. The linearity of the second scenario is between load angle and reference speed while the third one has a load angle–torque linear relationship which shows its optimality. Finally, the controlled characteristics and implementation for the optimum case are presented for both stationary and synchronous reference frames (for vector control purposes). Simulation modeling for optimum case is provided and its results match well with the proposed predictive control algorithm.

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Characterization of the parameters of interior permanent magnet synchronous motors for a loss model algorithm

Cited by 39 publications

References 25 publications

Energy Recovery Strategy Numerical Simulation for Dual Axle Drive Pure Electric Vehicle Based on Motor Loss Model and Big Data Calculation

Energy Recovery Strategy Numerical Simulation for Dual Axle Drive Pure Electric Vehicle Based on Motor Loss Model and Big Data Calculation

Energy‐saving system of secondary balance for the hybrid power of the pumping unit

Assessment of proposed maximum power point tracking–unity power factor algorithms for optimum operation permanent magnet synchronous generator–based wind turbine

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