Dynamic Supply Current Estimation for Electric Motor Drives

The patent introduces an intermediary estimation approach using a state observer and simplified plant model to infer supply current from measurable quantities (input voltage and inverter current). This mediator (the estimation algorithm) bridges the gap between available measurements and the desired supply current information without requiring direct sensing of the supply current itself.

The patent replaces the physical current sensor (mechanical/electrical measurement device) with a computational estimation system. Instead of using a hardware sensor to directly measure supply current, the system uses mathematical models and algorithms (state observer, plant model) to compute the supply current from other measurements, substituting physical measurement with computational inference.

The patent extracts only the essential dynamic elements (common mode choke and bulk capacitor) from the complete power input circuit model, removing unnecessary complexity while retaining the critical dynamics needed for accurate supply current estimation. This selective extraction maintains estimation precision while simplifying the model structure.

Instead of using a complex detailed model to achieve accuracy, the patent inverts the approach by using a simplified model that captures only the essential dynamics. The inversion lies in recognizing that fewer, more carefully selected model elements can achieve the same or better estimation accuracy by focusing on the dominant dynamic characteristics of the system.