Hybrid Petri Nets in Conceptual Schema of Dual-Motor Vehicle Synchronization

Motion generated components such as the driving and steering electric motors play a crucial role in the success and failure of any land vehicle mobility. For the driving motors, in-wheel hub adaptation has been widely favoured to replace traditional axle-driven vehicles. Additional steering motors are being coupled to combine two parallel drivelines to provide the extra degree of freedom movement per wheel. The implementation of multi-motor strategy would lead to an increase in vehicle part counts. This conceptual paper proposes a Petri net (PN) modelling approach to dual-motor framework of 4times4 vehicles consisting of an embedment instance of six propelled motors. Each preferred motor are accompanied by a three-phase inverter drive which is regarded as a discrete-event system. The motor drives are represented in the form of matrix depiction through event-driven nets and are paired with motors modelled via general stochastic nets. The dual-motor net framework with four-quadrant drive exemplifies motoring and regeneration operations and is used to investigate synchronization and asynchronization activities. The use of Petri net is seen as the de-facto standard methodology which supports modelling of vehicle structure and functional behaviour of multi-motor systems based on situations involving complex logical interactions of synchronization-related activities. Such modelling is intended to assist the multi-facet land vehicle in its complex initial system development. The main benefit of multiple PN motor drive characterization is that it provides insight about the properties and problems of the overall vehicle system prior to implementation. This allows many functional issues about the multi-facet land vehicle system to be resolved in the requirements and design phase rather than in the implementation phase. The construction of dual PN motor network are also intended for future extension to multiple motor net vehicle framework and use as fault models to improve the- - overall vehicle dependability by fault avoidance