Dependence of IPMSM Motor Efficiency on Parameter Estimates

Glac, Antonin; Šmı́dl, Václav; Peroutka, Zdeněk; Hackl, Christoph M.

doi:10.3390/su13169299

Cited by 4 publications

(3 citation statements)

References 28 publications

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“…This is simulated by setting smaller values of the inductances, with L s,d > L s,q , namely L s,d = 5 mH, L s,q = 3 mH. The resulting current trajectories for all tested algorithms and step change of the requested stator current from zero to [5,30]A are displayed in Figure 3. In this case, simplifications of the time-optimal trajectory differ from the proposed solution.…”

Section: Sensitivity Studymentioning

confidence: 99%

“…Optimization of the steady state operation is typically considered for permanent operation of the drive, with application to pumps or ventilation, hence the most common concern of optimization is efficiency [4,5]. However, this optimization is incomplete for highly dynamic operations such as robotic actuators or manipulators, where high precision of set-point tracking is required.…”

Section: Introductionmentioning

confidence: 99%

“…Figure 3. Comparison of studied versions of time-optimal control and deadbeat control on current reference step change from zero to[5, 30]A for modified parameters of the system with lower inductance at ω = 10 rad/s (top row), and ω = 250 rad/s (bottom row). The difference of the solutions in the origin is visible in open-loop strategy (left), its impact on the receding horizon reevaluation in each sampling period (right), sampling times are denoted by dots on the full lines.…”

mentioning

confidence: 99%

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Time-Optimal Current Control of Synchronous Motor Drives

2022

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We are concerned with the problem of fast and accurate tracking of currents in the general synchronous drive. The problem becomes complicated with decreasing available voltage, which is common in high-speed and field weakening regimes. The existing time-optimal controllers rely on a simplified model, ignoring stator resistance and differences in inductances. We derive a solution for the general model considering all parameters and show how the parameters affect the current trajectory. One simplifying assumption had to be made, but we show in simulation that it has a negligible impact on accuracy. The simplification allowed for the design of a feed-forward controller that has a low computational cost and can be easily implemented in realtime. We provide experimental validation of the controller on the developed IPMSM drive prototype of the rated power of 4.5 kW using conventional industrial DSP. The controller is compared to conventional PI and deadbeat solutions, demonstrating that the time-optimal controller can reach the required setpoint four times faster than the competitors at the field weakening regime of the drive. The proposed feed-forward control can be seen as a universal building block that can be combined with existing feedback controllers and observers and thus incorporated into existing control solutions.

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Section: Sensitivity Studymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

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Time-Optimal Current Control of Synchronous Motor Drives

2022

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Neural ODE for Estimation of Flux Linkage Models of Synchronous Machines

Ševčík,

Šmídl,

Glac

et al. 2023

IECON 2023- 49th Annual Conference of the IEEE Industrial Electronics Society

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Design of a Research Laboratory Drive System for a Synchronous Reluctance Motor for Vector Control and Performance Analysis

et al. 2021

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Motor-drive systems have the most significant share in industrial energy consumption, which requires a deep study in every aspect of the field. This paper presents a synchronous reluctance motor (SynRM) drive system based on Plecs RT box 1. The system’s design provides the opportunity for the open-loop and closed-loop control of the motor and a characteristic performance analysis of the motor. This paper focuses on the hardware implementation of a research laboratory setup and the precise vector control of the SynRM in real-time. The application of the digital controller and inverter to drive SynRM is examined. The voltage, current, and speed transducers were employed for monitoring the protective measures and to control the motor in the closed-loop. The design of the signal conditioning and the intermediary cards for isolation and data acquisition are described in detail. An algorithm is proposed to measure the whole system parameters, including motor, inverter, and cables. Thanks to the RT box 1, the principle of real-time simulation of control algorithms is investigated, and the rapid control prototyping of field-oriented control (FOC) of SynRM was implemented. The simulation of the system was carried out in the Plecs platform, and the results are presented. The experimental results of the implemented control algorithms validate the setup’s performance and the control algorithm. Finally, as a study of the motor’s performance, the efficiency map of the motor is drawn in different speed and torque ranges.

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Dependence of IPMSM Motor Efficiency on Parameter Estimates

Cited by 4 publications

References 28 publications

Time-Optimal Current Control of Synchronous Motor Drives

Time-Optimal Current Control of Synchronous Motor Drives

Neural ODE for Estimation of Flux Linkage Models of Synchronous Machines

Design of a Research Laboratory Drive System for a Synchronous Reluctance Motor for Vector Control and Performance Analysis

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