Virtual Calibration of xEV Thermal Management Systems

Written by Hanna Sara

June 14, 2021

Reducing the emission of the conventional vehicles by means of electrification of the powertrain brings new trends and new challenges for automotive engineers, especially in the field of thermal management and thermal component security. Thermal management systems for xEVs show a high degree of topological complexity, integration of new functions, more interaction between the different circuits, new thermal management strategies, and high level of complexity of the controls algorithms. The aim is to validate these new technologies early and without the presence of hardware, lowering the test costs and shortening development timeframes. Because of these requirements to design controls systems without prototype hardware, the focus is shifting to virtual testing (XiL) of vehicle systems: including Hardware in the Loop (HiL) and Software in the Loop (Sil) simulations.

XiL simulations tend to underline the software changes which may lead to the final market product. The key to keep pace with the changing requirements is efficient and simple workflow: minimization of modeling tools that are time intensive to interface, and a flexibility of a simulation model that allows for versatile model utilization of different stakeholders in an organization.  Ideally the same model would be used for detailed hydraulics, transient warmup component sizing, and controls’ development for HiL and SiL.

With GT-POWER-xRT, Gamma Technologies is offering a “settled in market” engine modeling tool, capable of bringing physical, predictive performance and combustion simulation on a HiL system. Similar opportunities exist for models for thermal management system or thermal component models. Delivering fast running thermal management models increases development efficiency and allows to explore new thermal management strategies.

With the increase demand for XiL cooling simulations, the ultimate objective is to be able to run the GT-SUITE cooling models on dedicated HiL machines.

GT-SUITE is capable to run fast, complex, and multi-physical thermal management models. The example that will be discussed is a Through The Road (TTR) hybrid vehicle with its thermal management system. The TTR powertrain has an ICE that drives one axle and an electric motor that drives the other. The plant includes a detailed thermal management system with:

  • 3DFE thermal representation of the engine
  • Detailed battery pack module
  • Quasi 3D Underhood model
  • Parametric thermal representation of the electric motor
  • Two-Phase system for battery cooling and passenger comfort
  • Cabin model
  • Detailed piping network for low and high temperature cooling circuits

Such a model is usually assembled by components and systems from several contributors, who may have different expectations on model accuracy and runtime. If the individual components and systems are not optimized for fast runtime, the resulting model will likely run slower than real time. In the described state, the example TTR model has a real time factor of 8:  meaning that it ran 8 times slower than real time. In order to make such a model accessible for stakeholders in SiL and HiL activities, GT-SUITE offers a set of comprehensive tools to guide through model changes while maintaining model accuracy.

For circuit setup, GT-SUITE is equipped with the “Circuit Definition” wizard to help identify the different numerical circuits in a system and set optimal and therefore fast numerical settings. In the TTR example the flow circuits are divided automatically between engine cooling, engine lubrication, battery cooling, e-motor cooling, underhood air, cabin air and the refrigerant. Through analysis of the model circuits GT-SUITE will select appropriate settings for fast model execution automatically.

Complex thermal management systems also contain a large number of flow volumes. The “Combine Flow Volume Wizard” is another tool within GT-SUITE that allows the user to reduce the total number of flow volumes for faster runtime. The wizard is a guided tool which in addition to automatically merging flow volumes also auto-calibrates the pressure drop of those simplified flow branch.  This automatic calibration maintains high result accuracy while decreasing the model runtime.

GT-SUITE also comes with a comprehensive tool for Design of Experiments. The user can perform any variation of the model inputs for the purpose of predicting the model outputs by means of a meta/surrogate model. In addition, the guided workflows as well as the visual and interactive plots facilitate the task and increase the work efficiency.

Another very useful tool for thermal management XiL modeling is GT-SUITE Integrated Optimizer which allows the user to automatically calibrate the models without any user interaction or guidance. The tool can also optimize the model to automatically achieve certain targets in Pareto-style optimizations, for example minimizing the warm-up time or maximizing the driving range.


When creating a thermal component model in GT-SUITE, e.g., of battery, e-machine or inverter, users typically capitalize on the GT-SUITE unique 1D-3D synergetic approach for fast runtimes with high accuracy. This approach usually results in a 1D flow network coupled to a full 3D-FEM thermal structure model which can be computationally expensive. To allow SiL and HiL stakeholders to efficiently work with those models, GT-SUITE allows changing the modeling approach from a 3D-FEM to a lumped thermal mass approach by the click of a button. The information needed to characterize a lumped thermal mass, such as distance to mass center and heat transfer areas, is extracted automatically from the 3D FE. With this new approach, the user does not have to maintain different models for component, SiL and HiL simulation.

Throughout the described stages, GT-SUITE’s FRM Converter offers a convenient way to organize files and view/compare results.

By using these GT-SUITE tools, we have derived, in a meaningful way, a fast-running simplified model from the previous detailed TTR example. The derived model has a real time factor of 0.7 while still respecting the physics of the model. Throughout the process, the fast-running model shows a high result accuracy when compared to the detailed model, as demonstrated in the following plots of the coolant, the battery, and the cabin temperature.

Because the physics of the system are maintained, the fast-running model keeps the predictability of the detailed physical model. For many late design changes during the project, such as scaling a heat exchanger or substituting the pump, fan, or valves, the derived fast-running model can predict the right behavior. To demonstrate this the HT radiator is scaled down in the detailed and in the fast-running TTR plant model. This scaled down heat exchanger will affect not only the heat transfer rate to the coolant, but also the air distribution in the underhood model, the power consumption of the pump and other important system parameters. The following plots prove that the simplified model keeps the high predictability level characteristic thanks to physics-based model optimization. The scaled down heat exchanger succeeded to predict and capture the same behavior of the heat transfer rate, the coolant temperature and the SOC of the battery in both models.

Finally, GT-SUITE’s flexibility allows to partition a full model into parallel sub-models by means of FMI, thereby allowing to utilize parallel cores on a HiL machine to further speed up model execution or run model with even higher physical modeling depth.

Utilizing GT-SUITE’s XiL tools for thermal system and component modeling enables efficient, accurate and convenient modeling including HiL applications. This allows physically descriptive and predictive models to be used throughout the engineering program. The following graph shows the results of the temperature of the engine, battery, and the cabin of the HiL capable TTR model over a WLTC cycle. At the end, the TTR detailed model runtime was reduced by 96% leading to HiL capable model run with a real time factor of 0.3.

In summary, GT-SUITE offers different ways to help the user transform their cooling model into a Real Time capable model. Gamma Technologies is committed to continue to develop new tools and improve its solution to provide the users the confidence to use the tool for their current projects and extend it to new usage in the future. For any questions or support related to runtime, please contact us at

Written by Hanna Sara