Assessment of Methods for the Real-Time Simulation of Electronic and Thermal Circuits

Abstract

Time–domain simulation of electronic and thermal circuits is required by a large array of applications, such as the design and optimization of electric vehicle powertrain components. While efficient execution is always a desirable feature of simulation codes, in certain cases like System-in-the-Loop setups, real-time performance is demanded. Whether real-time code execution can be achieved or not in a particular case depends on a series of factors, which include the mathematical formulation of the equations that govern the system dynamics, the techniques used in code implementation, and the capabilities of the hardware architecture on which the simulation is run. In this work, we present an evaluation framework of numerical methods for the simulation of electronic and thermal circuits from the point of view of their ability to deliver real-time performance. The methods were compared using a set of nontrivial benchmark problems and relevant error metrics. The computational efficiency of the simulation codes was measured under different software and hardware environments, to determine the feasibility of using them in industrial applications with reduced computational power.

Thermal Parameter and State Estimation for Digital Twins of E-Powertrain Components

“…The starting point for the computational methods in this paper is the modeling framework for electronic and thermal circuits introduced in [7], which represents a systematic way to assemble the dynamics circuit equations starting from its topology and component properties, although alternative descriptions could be used as well. Following this approach in the case of a thermal equivalent circuit, the variables used to describe the system are the temperature T of each node and the heat flow Q through every thermal resistor, source, and capacitor.…”

“…( 9) and (10) form a system of DAEs that is suitable to describe the dynamics of a wide array of electric, electronic, and thermal circuits in a straightforward way. They can be easily generated from system description and were used in [7] as the foundation of a general-purpose forward-dynamics circuit simulator. Section III below introduces a benchmark problem to illustrate the application of this modeling approach to a simple thermal network.…”

“…These components stand for thermal path resistances, inertias and losses, and they are connected to each other in the form of a resistive-capacitive (RC) network. LPTNs are modular and can be easily generated using a software library of components; they have also been shown to deliver RT performance when running on platforms with limited computational resources, such as ARM-based singleboard computers [7]. On the other hand, the fidelity with which they capture the real system behavior is critically dependent on the correctness of their topology and the accuracy with which their parameters are determined [8].…”

“…In this work, we put forward a framework to enable the consideration of thermal effects in DTs of e-powertrain components, using the Kalman filter to fuse numerical simulation results and temperature readings from the physical component under study. The starting point is a LPTN of the device, generated with a circuit simulation software tool [7]. The original LPTN dynamics, formulated using dependent variables as a system of differential algebraic equations (DAEs), is transformed into a system of ordinary differential equations (ODEs) more suitable for effective state and parameter estimation using a novel method introduced in this work.…”