Hybrid Dynamical Model for Reluctance Actuators Including Saturation, Hysteresis, and Eddy Currents

Ramirez-Laboreo, Edgar; Roes, M. G. L.; Sagüés, Carlos

doi:10.1109/tmech.2019.2906755

Cited by 30 publications

(22 citation statements)

References 40 publications

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“…Due to its complexity, magnetic hysteresis is most commonly ignored in this class q = 2 (motion) of actuators, even if its effect is not negligible. Still, there are some proposals for integrating magnetic hysteresis models into the dynamic system of reluctance actuators [22], [23].…”

Section: A Generalized Dynamicsmentioning

confidence: 99%

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Rauch-Tung-Striebel Smoother for Position Estimation of Short-Stroke Reluctance Actuators

Moya-Lasheras

Schellekens

Sagüés

2022

IEEE Trans. Contr. Syst. Technol.

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This paper presents a novel state estimator for shortstroke reluctance actuators, intended for soft-landing control applications in which the position cannot be measured in real time. One of the most important contributions regards the system modeling for the estimator. The discrete state of the hybrid system is treated as an input. Moreover, the model is simplified to facilitate the identification of parameters and the implementation of the estimator. Thus, auxiliary variables are added to the state vector in order to indirectly account for modeling errors. Another important contribution is the state estimation approach. It is based on the Rauch-Tung-Striebel fixed-interval smoother, which allows refining past data from later observations. Numerous simulations are performed to analyze and compare the proposal and several alternatives. In addition, experimental testing is presented to evaluate and validate the estimator. As the simulated and experimental analyses demonstrate, the combined effect of the novel additions results in significantly smaller estimation errors of position and velocity.

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Section: A Generalized Dynamicsmentioning

confidence: 99%

“…Note that e F does not only represent force deviations due to parametric or discretization errors, but also accounts for the normal forces during contact. As such, the transition function of the position (22) must also be tweaked to circumvent the removal of e F ,…”

Section: E Simulated Comparisonmentioning

confidence: 99%

Rauch-Tung-Striebel Smoother for Position Estimation of Short-Stroke Reluctance Actuators

Moya-Lasheras

Schellekens

Sagüés

2022

IEEE Trans. Contr. Syst. Technol.

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“…In order to compensate the effect of hysteresis during self-sensing, the hysteretic part of the incremental inductance needs to be separated from the non-hysteretic positiondependent part. This can be achieved by modeling a magnetic equivalent circuit, which has been proposed by many works such as [7,[29][30][31]. The magnetic circuit shown in Figure 10, consists of a MMF source as well as a magnetic reluctance for the iron core R mFe and the position dependent air gap reluctance R mx .…”

Section: Hysteresis Compensation Based On Magnetic Circuit Modelmentioning

confidence: 99%

“…Hysteresis modeling is well known in the state-of-the-art, as it is mostly applied in controllers to compensate for the hysteresis phenomena [28]. For the case of reluctance actuators, the work [29] shows the modeling of such kinds of actuators by means of the Generalized Preisach model for hysteresis. Similarly, the work [30] applies a Preisach model for observing the magnetic flux in the core and the air gap.…”

Section: Introductionmentioning

confidence: 99%

A Self-Sensing Method for Electromagnetic Actuators with Hysteresis Compensation

et al. 2021

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Self-sensing techniques are a commonly used approach for electromagnetic actuators since they allow the removal of position sensors. Thus, costs, space requirements, and system complexity of actuation systems can be reduced. A widely used parameter for self-sensing is the position-dependent incremental inductance. Nevertheless, this parameter is strongly affected by electromagnetic hysteresis, which reduces the performance of self-sensing. This work focuses on the design of a hysteresis-compensated self-sensing algorithm with low computational effort. In particular, the Integrator-Based Direct Inductance Measurement (IDIM) technique is used for the resource-efficient estimation of the incremental inductance. Since the incremental inductance exhibits a hysteresis with butterfly characteristics, it first needs to be transformed into a B-H curve-like hysteresis. Then, a modified Prandtl–Ishlinskii (MPI) approach is used for modeling this hysteretic behavior. By using a lumped magnetic circuit model, the hysteresis of the iron core can be separated from the air gap, thus allowing a hysteresis-compensated estimation of the position. Experimental studies performed on an industrial switching actuator show a significant decrease in the estimation error when the hysteresis model is considered. The chosen MPI model has a low model order and therefore allows a computationally lightweight implementation. Therefore, it is proven that the presented approach increases the accuracy of self-sensing on electromagnetic actuators with remarkable hysteresis while offering low computational effort which is an important aspect for the implementation of the technique in cost-critical applications.

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“…In contrast, when using FEA, although the analysis speed is slow, nonlinear magnet saturation characteristics can be reflected. Therefore, EV traction motors, which necessitate excellent nonlinear magnetic saturation characteristics, are primarily designed using FEA [4][5][6][7].…”

Section: Introductionmentioning

confidence: 99%

Robust Explorative Particle Swarm Optimization for Optimal Design of EV Traction Motor

Lee¹,

Kim²,

Jung

2021

Processes

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This paper proposes a robust optimization algorithm customized for the optimal design of electric machines. The proposed algorithm, termed “robust explorative particle swarm optimization” (RePSO), is a hybrid algorithm that affords high accuracy and a high search speed when determining robust optimal solutions. To ensure the robustness of the determined optimal solution, RePSO employs the rate of change of the cost function. When this rate is high, the cost function appears as a steep curve, indicating low robustness; in contrast, when the rate is low, the cost function takes the form of a gradual curve, indicating high robustness. For verification, the performance of the proposed algorithm was compared with those of the conventional methods of robust particle swarm optimization and explorative particle swarm optimization with a Gaussian basis test function. The target performance of the traction motor for the optimal design was derived using a simulation of vehicle driving performance. Based on the simulation results, the target performance of the traction motor requires a maximum torque and power of 294 Nm and 88 kW, respectively. The base model, an 8-pole 72-slot permanent magnet synchronous machine, was designed considering the target performance. Accordingly, an optimal design was realized using the proposed algorithm. The cost function for this optimal design was selected such that the torque ripple, total harmonic distortion of back-electromotive force, and cogging torque were minimized. Finally, experiments were performed on the manufactured optimal model. The robustness and effectiveness of the proposed algorithm were validated by comparing the analytical and experimental results.

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Hybrid Dynamical Model for Reluctance Actuators Including Saturation, Hysteresis, and Eddy Currents

Cited by 30 publications

References 40 publications

Rauch-Tung-Striebel Smoother for Position Estimation of Short-Stroke Reluctance Actuators

Rauch-Tung-Striebel Smoother for Position Estimation of Short-Stroke Reluctance Actuators

A Self-Sensing Method for Electromagnetic Actuators with Hysteresis Compensation

Robust Explorative Particle Swarm Optimization for Optimal Design of EV Traction Motor

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