Modeling of a Four-Phase 8/6 Switched Reluctance Motor

Switched Reluctance Motors (SRMs) are widely used in industrial drives due to their simple structure, high reliability, and strong adaptability. The four-phase 8/6 configuration represents a common SRM topology, whose modeling is crucial for performance analysis, control strategy design, and operational optimization.

Basic Model Structure The four-phase 8/6 SRM consists of a stator, rotor, and four-phase windings. The stator typically has 8 poles while the rotor has 6 poles (8/6 structure), forming four independent excitation circuits. The core of the motor model lies in describing the relationships between flux linkage, torque, current, and rotor position. In code implementation, this requires maintaining state variables for each phase's current and the rotor's angular position.

Mathematical Representation of Motor Model The dynamic model can be described through voltage equations, mechanical motion equations, and flux linkage characteristics: Voltage Equation: Each phase's voltage equation relates to inductance, resistance, and current variation, typically including back-EMF effects. Implementation requires solving differential equations for each phase using numerical methods like Runge-Kutta. Torque Equation: Torque is determined by the partial derivative of magnetic co-energy with respect to rotor position, proportional to the square of current and influenced by rotor position. Code implementation often uses look-up tables or analytical functions for torque calculation. Mechanical Equation: Describes rotor motion, incorporating effects of load torque, inertia, and damping. This is typically implemented as a second-order differential equation solved simultaneously with electrical equations.

Torque and Electrical Parameter Measurement Torque measurement typically requires calculations combining current, rotor position, and inductance characteristics. Instantaneous torque values can be derived from current and position sensor data using pre-established flux-linkage-current-position (ψ-i-θ) lookup tables or analytical models. In simulation code, this involves interpolation algorithms for table lookups or real-time computation of electromagnetic torque.

Voltage and current measurements are acquired directly through sensors for analyzing input power, losses, and efficiency. Current waveforms reflect winding conduction states and commutation logic, while voltage waveforms assess drive circuit performance. Data acquisition code typically includes filtering algorithms and synchronization with position signals.

Simulation and Practical Applications In simulation, high-precision models can be established using Finite Element Analysis (FEA) or equivalent magnetic circuit methods to predict static and dynamic characteristics. Practical testing requires data acquisition systems (like DAQ) to record voltage, current, and position signals in real-time for model validation. Simulation code often integrates with FEA results through parameter extraction and co-simulation techniques.

By establishing an accurate four-phase 8/6 SRM model, theoretical basis can be provided for high-performance control strategies (such as Direct Instantaneous Torque Control) while optimizing operational efficiency and dynamic response. Control algorithm implementation typically requires real-time computation of reference currents and optimal switching patterns.