Comprehensive System to Component xEV Simulation Using GT-SUITE and JMAG (Part II)

Written by Michael Zagun and Yusaku Suzuki

August 6, 2020
Battery Thermal Management Simulation

This second blog of our two-part series on system to component xEV simulation looks at a solution approach which goes beyond the scope of basic energy consumption evaluation.

Once the electric machine has been preselected based on the map-based approach – taking into account the energy consumption and packaging aspects, as shown in part 1 of this blog series – the peripherals (inverter, dc-link filter) and the associated control strategy must be designed and fine-tuned. This helps to ensure that the operational machine efficiency is high during transient operation and the current profile discharged from the battery is smooth, which are important factors for both achievable total energy consumption and component health. These development tasks are mastered with the help of electrical-equivalent system models.

Options for integrating JMAG-Express Online models with GT-SUITE system models

The integration of JMAG-Express Online with GT-SUITE basically allows two options to create such an electric-equivalent model of the electric machine, depending on the availability of data, on simulation models already in place or your preference for modeling features.

The first option is preferable for a simulation driven design evaluation chain and conducts the transformation of the FE based JMAG-Express Online model into a JMAG-RT plant model. The JMAG-RT plant model integrates directly into the system model of the electrical, mechanical and thermal domain within GT-SUITE and includes detailed specifications regarding the electrical equivalent machine attributes and the associated thermal losses throughout the entire operation range of the machine.

The second option is available when you would like to customize the level of model fidelity or include machine parameter values obtained from measurements. This approach is based on the export of the electrical-equivalent machine parameters from JMAG-Express Online into the appropriate electric machine template in GT-SUITE.

Both electrical-equivalent machine modeling options require an electrical excitation: in the simplest case using an AC voltage source, for the purpose to estimate the resulting mechanical performance of the machine. This idealized setup of the electrical domain allows engineers to design and optimize the control strategy which is required to drive the electric machine.

JMAG-RT-Part-1-Model-Map
JMAG-RT-Part-2-Machine-Constants

Control Strategy Design in GT-SUITE

The signal flow diagram in the figure below represents a field-oriented control strategy with PI based current controllers. It contains two blocks for the Clarke-Park Transformation which transform the sensed 3-phase current signals to the rotor-oriented d-q reference frame and reversely transform the controller d-q voltage outputs to the 3-phase system. The target value generator includes the core strategy to satisfy a high electric machine efficiency in both the base speed and the field-weakening region.

In a further detailing step, the system model can be expanded to include a switching inverter model and the associated control strategy (e.g. Pulse Width Modulation). This level of model fidelity allows users to explore the full detail of system dynamics both in the electrical and the mechanical domain. Therefore, you may find all relevant control blocks ready-to-use inside the GT-SUITE Template Library and start from the exemplary control circuits contained in the numerous example models and refine them for your individual needs.

It is obvious that the electrical equivalent approach adds a deep insight into the interplay of the electrical components and their control strategy. It complements the map-based approach depending on the data availability and requirements at the particular development stages. Both approaches are successfully conducted through the integration of JMAG-Express Online with GT-SUITE, taking advantage of a good degree of automation.

Written By: Michael Zagun and Yusaku Suzuki