摘要:
This paper presents a comprehensive evaluation of system interactions in a battery electric vehicle caused by temperature sensitivity of permanent magnet synchronous machines (PMSM). An analytical model of a PMSM considering iron losses and thermal impact is implemented on a field programmable gate array suitable for hardware-in-the-loop testing. By the presented virtual prototyping approach, different machine characteristics defined by the design are used to parameterize the analytical model. The investigated temperature effect is understood as an interacting influence between machine characteristics and control, which are investigated in terms of torque generation, voltage utilization and efficiency under closed-loop condition in a vehicle environment. In particular, using a surface permanent magnet rotor and an interior permanent magnet rotor, the performance of both machine designs is analyzed by varying temperature-adjusted feedforward control strategies on the basis of a driving cycle from a racetrack. The comparison shows that the machine design with surface-mounted magnets is associated with higher temperature sensitivity. In this case, the temperature consideration in the feedforward control provides a 14% loss reduction in closed-loop vehicle test operation. It can be summarized that the electromagnetic torque is less sensitive to a temperature variation with increasing reluctance. The presented development approach demonstrates the impact of interactions in electric powertrains without the need of real prototypes.
René Scheer, Yannick Bergheim, Simon Aleff, Daniel Heintges, Niclas Rahner, Rafael Gries & Jakob Andert .
A Virtual Prototyping Approach for Development of PMSM on Real-Time Platforms: A Case Study on Temperature Sensitivity
[J]. Automotive Innovation, 2022, 5(3): 285-298.
René Scheer, Yannick Bergheim, Simon Aleff, Daniel Heintges, Niclas Rahner, Rafael Gries & Jakob Andert .
A Virtual Prototyping Approach for Development of PMSM on Real-Time Platforms: A Case Study on Temperature Sensitivity
[J]. Automotive Innovation, 2022, 5(3): 285-298.