J.N. Ross

Optimizing the Jiles-Atherton model of hysteresis by a genetic algorithm

Modeling magnetic components for simulation in electric circuits requires an accurate model of the hysteresis loop of the core material used. It is important that the parameters extracted for the hysteresis model be optimized across the range of operating conditions that may occur in circuit simulation. This paper shows how to extract optimal parameters for the Jiles-Atherton model of hysteresis by the genetic algorithm approach. It compares performance with the well-known simulated annealing method and demonstrates that improved results may be obtained with the genetic algorithm. It also shows that a combination of the genetic algorithm and the simulated annealing method can provide an even more accurate solution than either method on its own. A statistical analysis shows that the optimization obtained by the genetic algorithm is better on average, not just on a one-off test basis. The paper introduces and applies the concept of simultaneous optimization for major and minor hysteresis loops to ensure accurate model optimization over a wide variety of operating conditions. It proposes a modification to the Jiles-Atherton model to allow improved accuracy in the modeling of the major loop.

Simulation of magnetic component models in electric circuits including dynamic thermal effects

It is essential in the simulation of power electronics applications to model magnetic components accurately. In addition to modeling the nonlinear hysteresis behavior, eddy currents and winding losses must be included to provide a realistic model. In practice the losses in magnetic components give rise to significant temperature increases which can lead to major changes in the component behavior. In this paper a model of magnetic components is presented which integrates a nonlinear model of hysteresis, electro-magnetic windings and thermal behavior in a single model for use in circuit simulation of power electronics systems. Measurements and simulations are presented which demonstrate the accuracy of the approach for the electrical, magnetic and thermal domains across a variety of operating conditions, including static thermal conditions and dynamic self heating.

Modelling battery charge regulation for a stand-alone photovoltaic system

Abstract A new model for the charge and discharge characteristics of a lead–acid battery is presented which aims to model the effect on capacity of variable charge and discharge rates. This model has been implemented using the circuit simulator PSPICE, and is used to investigate the effect of the charge controller strategy on the performance of a stand-alone PV system. It is shown that a simple limit on charging voltage is probably adequate to achieve a high state of charge, although a two-level regulator may be needed to maintain battery condition. The benefits of maximum power point tracking are also investigated.

Modeling frequency-dependent losses in ferrite cores

We suggest a practical approach for modeling frequency-dependent losses in ferrite cores for circuit simulation. Previous work has concentrated on the effect of eddy-current losses on the shape of the B--H loop, but in this paper we look at the problem from the perspective of energy loss and propose a different network for accurately modeling power loss in ferrite cores. In power applications, the energy loss across the frequency range can have a profound effect on the efficiency of the system, and a simple ladder network in the magnetic domain is not always adequate for this task. Simulations and measurements demonstrate the difference in this approach from the RL ladder network models both in the small-signal and large-signal contexts.

Definition and application of magnetic material metrics in modeling and optimization

The modeling of magnetic components for use in electrical circuit simulation requires that the core material be accurately characterized. This paper investigates a method of extracting parameters to model the hysteresis behavior of magnetic core materials and optimizing them to achieve accurate results during circuit simulation. Metrics are defined to measure specific features of the behavior of both the core magnetic material and the magnetic component, such as a transformer. This paper presents a method of applying these metrics for the purposes of comparison and optimization and demonstrates the method using measured results and corresponding simulations. It compares the effectiveness of a weighted metrics function with that of a least squares goal function for the purpose of optimization. This paper suggests modifications to the original Jiles-Atherton model to improve the ability of the model to more accurately represent the behavior of magnetic materials during saturation.

Magnetic material model characterization and optimization software

The accurate characterization and modeling of magnetic materials are critical in simulating the performance analysis of electrical circuits incorporating magnetic components. Software has, therefore, been developed, including genetic algorithm-optimization techniques and metric-based goal functions to enable appropriate accuracy in the final model. Multiple loop optimization has been developed to allow a wide range of operating conditions to be used in the goal function, with appropriate weighting for the ultimate application. Sensitivity and Monte Carlo analyses ensure the models are stable and tolerant of parameter variations. Comparisons of simulated B-H curves with measured results demonstrate the capability of the software.

Predicting total harmonic distortion in asymmetric digital subscriber line transformers by simulation

As a design application, the asymmetric digital subscriber line (ADSL) broad-band line transformer offers somewhat different challenges than those in power supply design. In this paper, we use simulation to analyze total harmonic distortion (THD) as affected by the nonlinear behavior of the magnetic material in a line transformer. We use a mixed-technology model of the line transformer and circuit simulation to predict the level of THD for a variety of core types and configurations. A comparison of the simulation results with measured THD figures demonstrates the accuracy of the models.

Behavioural modelling of operational amplifier faults using analogue hardware description languages

The use of behavioural modelling for operational amplifiers has been well known for many years and previous work has included modelling of specific fault conditions using a macro-model. In this paper, the models are implemented in a more abstract form using analogue hardware description languages (HDL), including MAST, taking advantage of the ability to control the behaviour of the model using high-level fault condition states. The implementation method allows a range of fault conditions to be integrated without switching to a completely new model. The various transistor faults are categorised, and used to characterise the behaviour of the HDL models. Simulations compare the accuracy and speed of the transistor and behavioural level models under a set of representative fault conditions.

Efficient mixed-domain behavioural modelling of ferromagnetic hysteresis implemented in VHDL-AMS

In this paper, a modified model of ferromagnetic hysteresis suitable for mixed-signal simulations in VHDL-AMS is presented. The aim of this paper is to demonstrate how a numerically stable and accurate implementation of the Jiles-Atherton model can be achieved using a 4th order Runga-Kutta integration of the derivative of magnetization with respect to the field strength (H). While most SPICE-like implementations require inconvenient integration in time to obtain the magnetization derivative, our approach is more general as it does not rely on the underlying differential equation solver for this purpose. The model addresses the non-physical situation of negative BH slopes and proposes an alternative implementation of the anhysteretic function using a polynomial approximation of the Langevin function for low signal levels and a new function with no discontinuities. Model efficiency is improved by monitoring the change in H and only activating the integration function when H changes by a specified amount.

Dynamic electrical-magnetic-thermal simulation of magnetic components

This paper describes how the modeling and simulation of electromagnetic devices can be extended to include dynamic thermal effects. The power generated by hysteresis inside ferrite cores is connected to a thermal model of the core material. The thermal conduction of the core material is modeled as is the convection of thermal energy from the core to the surrounding environment. The effective temperature change inside the core is used to modify the parameters of the core material model to accurately reflect the dynamic performance of the device at all temperatures. The electrical circuit, magnetic material and thermal networks are all modeled concurrently in the time domain to allow dynamic interactions across all three domains.