Modeling of Multiple-Input DC-DC Converters Considering Input-Coupling Effects

This paper studies modeling of multiple-input converters (MICs). Many MICs are based on a time division multiplexing scheme. In the dynamic equations of such an MIC, a state variable from one input leg is possible to be affected by state variables from other input cells, and all the switching functions. In this way, inputs are coupled both topologically and from control actions through switching functions. Input-coupling effects complicate MICs' behavior. Consequently, substantial modeling errors may occur when classical averaging approach is utilized to model an MIC even with moderately high switching frequencies or small ripples. The errors may increase with incremental number of input legs. In addition to demonstrating the special features on MIC modeling, this paper utilizes the generalized averaging approach to generate a more accurate model, which is also used to derive a small signal model. The proposed model is an important tool that yields better results when analyzing power budgeting, performing large-signal simulations and designing controllers for MICs via a more precise representation than classical averaging methods. All these analyses are supported by simulations and experimental results.