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This paper aims to develop mathematical models of variously compensated wireless energy transfer (WET) systems. Attention is primarily paid to the derivation of the most important energy transfer characteristics such as efficiency and amount of transferred power. This paper discusses the main advantages and disadvantages of various compensation techniques to show their possible application areas. On the basis of these results, a designer will be able to quickly identify which compensation type suites as the best solution to fulfill a given system’s requirements.

First, the current state in the field of mathematical modeling of WET systems is introduced. Next, the non-resonant magnetic-coupled circuit together with four most common resonant magnetic-coupled circuits is analyzed. The equivalent circuit models using loop currents methodology is applied to the analyses. The proposed methodology is experimentally verified by the laboratory measurement of selected circuit topology. The main contribution of the proposed methodology lies in its quick applicability on more complicated or extended systems while keeping a relatively good match with the real system’s behavior.

The authors have presented the usage of a simple and accurate methodology for investigating variously compensated WET systems. Electrical engineers who require effective and powerful tools for the identification of basic WET systems properties will find this methodology to be of extensive help.

The analyses consider only the sinusoidal type of supply voltage; so, it is valid mainly for the close range of the resonant state. Nonlinearities cannot be taken into account.

This research may be applied in the field of WET systems.

Research in the area of power electronic systems, which provides a clear and straightforward procedure for WET system identification, will be helpful to most practical technicians who are not well versed in areas of physical-based phenomena.

Outlines Heath, Jarrow and Morton’s (1992) method (MJM) for modelling interest rates and refers to other research showing that although it is generally non‐Markov, this can be modified if the volatility structure depends on relative maturity term rather than calendar maturity date. Develops a re‐indexed MJM model, applies it to 1975‐1991 data on non‐callable US treasury bills, notes and bonds; and compares its goodness of fit with Jordan (1984). Finds the forward function consistent with constant parameters, that state variables can be identified from the cross‐section estimates and that they have zero mean first differences when analysed through time series. Concludes that the forward function follows a martingale and promises further research.