Implementation of vehicle simulation model in a modern dynamometer test environment

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Tamás Koller
Csaba Tóth-Nagy
József Perger


The rapid development of digital technology makes it possible to expand the sustainability of the transport sector.  With the development of digitalization, virtual tests play an increasingly important role in product design. With the development of computer technology, there is a more accurate and faster opportunity to save time, energy, and costs before the product is introduced to the market. In the early stages, vehicle simulation can be effectively used, which is a cost- and time-efficient solution. This study presents the transfer of a vehicle simulation model to an internal combustion engine dynamometer. Dynamometers allow the behavior of the real engine to be tested before the complete vehicle is available. Building the simulation model of the complete system including the dynamometer and the engine makes it possible to setup the variables of the real test environment resulting in decreased time and cost on the dynamometer. Furthermore, the system constructed in this way can be suitable for carrying out the tests that were previously carried out on the entire vehicle. With a vehicle simulation model, the level of simulation can be changed as needed during development until the developed real vehicle is fully realized.

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How to Cite
Koller, T., Tóth-Nagy, C., & Perger, J. (2022). Implementation of vehicle simulation model in a modern dynamometer test environment. Cognitive Sustainability, 1(4).


Petters J. (2019). RDE-Optimierung mittels Abbildung verschiedener Fahrercharakteristiken. In: Liebl, J. (Hrsg.). Simulation und Test 2018. Springer Vieweg, Wiesbaden. DOI:

Zöldy, M., Baranyi, P. (2021). Cognitive Mobility – CogMob. In: Nikodem, J., Klempous, R. (eds). 12th IEEE International Conference on Cognitive Infocommunications (CogInfoCom 2021). Proceedings IEEE. 921–925.

Baranyi, P., Csapo, A. (2010). Cognitive Infocommunications: CogInfoCom. 2010 11th International Symposium on Computational Intelligence and Informatics (CINTI). 141–146. DOI:

Dietrich M., Rupfle, J. (2020). Der Antriebsprüfstand als Plattform für die RDE-Emissionierung. In: Liebl, J. (Hrsg..). Experten-Forum Powertrain: Simulation und Test 2019. Springer Vieweg, Wiesbaden. 137–152. DOI:

Pfister F. (2019). Connected Testing of ADAS and Powertrain Functions on Integration Test Beds. 8th International Symposium on Development Methodology: IPG Automotive GmbH.

Jiang S., Smith, M., Kitchen, J., Ogawa (2009). Development of an Engine-in-the-loop Vehicle Simulation System in Engine Dynamometer Test Cell. SAE Technical Paper. DOI:

Nyerges, Á, Zöldy, M. (2020). Verification and Comparison of Nine Exhaust Gas Recirculation Mass Flow Rate Estimation Methods. Sensors. 20(24). 7291. DOI:

Bauer, S., Beidl, C., Laubis, K., Keuth, N. (2019). RDE Evaluation by Efficient Fleet Data Management and Advanced Analytics. 8th International Symposium on Development Methodology: IPG AutomotiveGmbH.

Jung, T., Kötter, M., Schaub, J. Quérel, C., Thewes, S., Hadj-amor, H., Picard, M., Lee, S-Y. (2019). Engine-in-the-Loop: A Method for Efficient Calibration and Virtual Testing of Advanced Diesel Powertrains, Simulation und Test 2018. Springer Fachmedien, Wiesbaden. DOI:

Teuschl, G., Jung, C., Ellinger, R., Ebner, P., Huss, A., Merl, R. (2021). Model Based xEV Test and Calibration. Benefits and Limitations. In: Liebl, J., Beidl, C., Maus, W. (Hrsg.). Internationaler Motorenkongress 2021. Wiesbaden : Springer Fachmedien Wiesbaden GmbH, ein Teil von Springer Nature, DOI:

Yao, L., Wu, J., Wang, Y., Liu, C. (2014). Research on vehicle integrated control algorithm based on MATLAB and CANoe co-simulation. 2014 IEEE Conference and Expo Transportation Electrification Asia-Pacific (ITEC Asia-Pacific). 1–5. DOI: