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For large and small signal analysis of electromechanical systems with power electronic devices such as Brushless DC (BLDC) motor-inverter drives, average-value models (AVMs) are indisputable. Average-value models are typically orders of magnitude faster than the corresponding detailed models. This advantage makes AVMs ideal for representing motor-drive components in system level studies. Derivation of accurate dynamic average-value model of BLDC motor-drive system is generally challenging and requires careful averaging of the stator phase voltages and currents over a prototypical switching interval (SI) to find the corresponding average-value relationships for the state variables and the resulting electromagnetic torque. The so-called 120° voltage source inverter (VSI) driven brushless dc (BLDC) motors are very common in many commercial and industrial applications. This thesis extends the previous work and presents a new and improved dynamic average-value model (AVM) for such BLDC motor-drive systems. The new model is explicit and uses a proper model of the permanent magnet synchronous machine with non-sinusoidal rotor flux. The model utilizes multiple reference frame theory to properly include the back EMF harmonics as well as commutation and conduction intervals into the averaged voltage and torque relationships. The commutation angle is readily obtained from the detailed simulation. The proposed model is then demonstrated on two typical industrial BLDC motors with differently-shaped back EMF waveforms (i.e. trapezoidal and close to sinusoidal). The results of studies are compared with experimental measurements as well as previously established state-of-the-art models, whereas the new model is shown to provide appreciable improvement especially for machines with pronounced trapezoidal back EMF.