Abstract
Geographically distributed hardware-in-the-loop (HIL) testing has the potential to allow hybrid vehicle powertrain components (battery, motor drive, and engine) to be developed at geographically remote locations but tested concurrently and coupled. Inter-location internet communication links can allow non-ideal behaviour observed in a physical component in one location (e.g. an electrical drive) to be imposed on another physical component elsewhere (e.g. an ICE), and vice-versa. A key challenge is how to represent the behaviour of a remote, physical component under testing in a local HIL environment. Internet communications are too slow and unreliable to transmit waveforms in real-time and so one solution is to use a local ‘slave’ model whose behaviour and parameters are tuned based on observations at the remote location. This study proposes a multi-frequency averaging (MFA) slave model of an electric motor drive system for use in this application; it addresses a weakness in previously published work by extending the MFA model to variable frequency operation. The model was benchmarked against experimental operation (and its equivalent simulation model) in open-loop and closed-loop space vector pulse-width modulation control strategy, fixed and variable frequency operation. Results show significant reconciliation of model and experiment.
Highlights
The modern automotive industry has increasingly shifted to electrified powertrains in the quest for environmental sustainability
All sub-systems are co-located for system prototype testing all throughout its development, but this is expensive and time-consuming especially for the automotive industry since they are usually developed under different roofs and often by different companies/suppliers who are bound by confidentiality clauses
Hardware-in-the-loop (HIL) testing has helped by allowing a single sub-system prototype to be loaded by the test-rig which behaves as the remainder of the system
Summary
The modern automotive industry has increasingly shifted to electrified powertrains in the quest for environmental sustainability. It was quickly understood that for electrical systems, exchanging signals in frequency-domain (i.e. amplitudes of harmonics of interest as a function of time or dynamic phasors) is advantageous since the variables change rapidly, their component phasors are slow and specific This helps by reducing the system time constants (increasing simulation speed) and reducing the sensitivity of waveform reproduction accuracy on communication delays. Minimal model complexity is needed for real-time simulation These three requirements led to the identification of multi-frequency averaging (MFA; terminology interchangeably used with generalised average modelling and dynamic phasors in the research community) as the underlying methodology for the remote observer model of an automotive epowertrain. A recent work [1] by the authors has introduced the motivation behind using MFA for the remote observer model of a generic e-powertrain and validated its variable frequency operation against high-fidelity switching model simulation results. Benchmarking studies and results follow with conclusions marking the end of the paper
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