Skip to main content

27.11.2024 | Electric, Fuel Cell, and Hybrid Vehicle, Transmission and Driveline

MPC Energy Prediction Control Simulation of a Hybrid Electric Vehicle

verfasst von: Jinkyeom Cho, Hyeongcheol Lee

Erschienen in: International Journal of Automotive Technology

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

The paper presents a model predictive control (MPC) energy prediction control function simulation environment using virtual controller technology. The MPC energy prediction function is a fuel economy improvement function applied to the hybrid control unit (HCU) of the Hyundai Santa Fe. This function uses the gradient and average speed information of the upcoming road to perform optimal driving point control of the engine and motor of the hybrid electric vehicle (HEV) based on the expected required power. The components of the simulation environment are HCU virtual controllers, vehicle models, roads, and navigation. Virtual controllers were created using virtual controller technology based on HCU mass production codes. The vehicle model is a Transmission Mounted Electric Device (TMED) system with the powertrain specifications of a Hyundai Santa Fe Hybrid. Road and navigation information was collected using actual vehicle test data. The consolidation of the simulation environment was confirmed by comparing the actual vehicle test data and simulation data, such as the vehicle model, MPC energy prediction control function and fuel economy model. As a result of the simulation, the characteristics of the MPC energy prediction control were confirmed and the fuel economy improved to similar to that of the vehicle test using a robot driver.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

ATZelectronics worldwide

ATZlectronics worldwide is up-to-speed on new trends and developments in automotive electronics on a scientific level with a high depth of information. 

Order your 30-days-trial for free and without any commitment.

Weitere Produktempfehlungen anzeigen
Literatur
Zurück zum Zitat Broy, M., Kirstan, S., Krcmar, H., & Schätz, B. (2012). What is the benefit of a model-based design of embedded software systems in the car industry?. In Emerging technologies for the evolution and maintenance of software models, 343–369 Broy, M., Kirstan, S., Krcmar, H., & Schätz, B. (2012). What is the benefit of a model-based design of embedded software systems in the car industry?. In Emerging technologies for the evolution and maintenance of software models, 343–369
Zurück zum Zitat De Souza, G., Odloak, D., & Zanin, A. C. (2010). Real time optimization (RTO) with model predictive control (MPC). Computers & Chemical Engineering, 34(12), 1999–2006.CrossRef De Souza, G., Odloak, D., & Zanin, A. C. (2010). Real time optimization (RTO) with model predictive control (MPC). Computers & Chemical Engineering, 34(12), 1999–2006.CrossRef
Zurück zum Zitat Kim, D., Eo, J. S., & Kim, K. K. K. (2021). Service-oriented real-time energy-optimal regenerative braking strategy for connected and autonomous electrified vehicles. IEEE Transactions on Intelligent Transportation Systems, 23(8), 11098–11115.CrossRef Kim, D., Eo, J. S., & Kim, K. K. K. (2021). Service-oriented real-time energy-optimal regenerative braking strategy for connected and autonomous electrified vehicles. IEEE Transactions on Intelligent Transportation Systems, 23(8), 11098–11115.CrossRef
Zurück zum Zitat Kumar, A. S., & Ahmad, Z. (2012). Model predictive control (MPC) and its current issues in chemical engineering. Chemical Engineering Communications, 199(4), 472–511.CrossRef Kumar, A. S., & Ahmad, Z. (2012). Model predictive control (MPC) and its current issues in chemical engineering. Chemical Engineering Communications, 199(4), 472–511.CrossRef
Zurück zum Zitat Lu, J., Hong, S., Sullivan, J., Hu, G., Dai, E., Reed, D., & Baker, R. (2017). Predictive transmission shift schedule for improving fuel economy and drivability using electronic horizon. SAE International Journal of Engines, 10(2), 680–688.CrossRef Lu, J., Hong, S., Sullivan, J., Hu, G., Dai, E., Reed, D., & Baker, R. (2017). Predictive transmission shift schedule for improving fuel economy and drivability using electronic horizon. SAE International Journal of Engines, 10(2), 680–688.CrossRef
Zurück zum Zitat Masoudi, Y., & Azad, N. L. (2017). MPC-based battery thermal management controller for plug-in hybrid electric vehicles. In 2017 American Control Conference (ACC), 4365–4370. Masoudi, Y., & Azad, N. L. (2017). MPC-based battery thermal management controller for plug-in hybrid electric vehicles. In 2017 American Control Conference (ACC), 4365–4370.
Zurück zum Zitat Ozkan, M.F. & Ma, Y. (2021). Fuel-economical distributed model predictive control for heavy-duty truck platoon. In: 2021 IEEE International Intelligent Transportation Systems Conference (ITSC). IEEE, 2021. p. 1919-1926 Ozkan, M.F. & Ma, Y. (2021). Fuel-economical distributed model predictive control for heavy-duty truck platoon. In: 2021 IEEE International Intelligent Transportation Systems Conference (ITSC). IEEE, 2021. p. 1919-1926
Zurück zum Zitat Park, S., & Ahn, C. (2020). Computationally efficient stochastic model predictive controller for battery thermal management of electric vehicle. IEEE Transactions on Vehicular Technology, 69(8), 8407–8419.CrossRef Park, S., & Ahn, C. (2020). Computationally efficient stochastic model predictive controller for battery thermal management of electric vehicle. IEEE Transactions on Vehicular Technology, 69(8), 8407–8419.CrossRef
Zurück zum Zitat Pisaturo, M., & Senatore, A. (2019). Thermal compensation control strategy in automated dry clutch engagement dynamics and launch manoeuvre. International Journal of Automotive Technology, 20, 1089–1101.CrossRef Pisaturo, M., & Senatore, A. (2019). Thermal compensation control strategy in automated dry clutch engagement dynamics and launch manoeuvre. International Journal of Automotive Technology, 20, 1089–1101.CrossRef
Zurück zum Zitat Sciarretta, A., & Guzzella, L. (2007). Control of hybrid electric vehicles. IEEE Control Systems Magazine, 27(2), 60–70.CrossRef Sciarretta, A., & Guzzella, L. (2007). Control of hybrid electric vehicles. IEEE Control Systems Magazine, 27(2), 60–70.CrossRef
Zurück zum Zitat Song, D., Bi, D., Zeng, X., & Wang, S. (2023). Energy management strategy of plug-in hybrid electric vehicles considering thermal characteristics. International Journal of Automotive Technology, 24(3), 655–668.CrossRef Song, D., Bi, D., Zeng, X., & Wang, S. (2023). Energy management strategy of plug-in hybrid electric vehicles considering thermal characteristics. International Journal of Automotive Technology, 24(3), 655–668.CrossRef
Zurück zum Zitat SYNOPSYS (2023). Synopsys Automotive VDK for Level 4 Virtual ECU Abstraction. INFO SHEET-JAN-2023 SYNOPSYS (2023). Synopsys Automotive VDK for Level 4 Virtual ECU Abstraction. INFO SHEET-JAN-2023
Zurück zum Zitat Yang, I., Jeon, W. H., & Lee, H. M. (2017). A study on dynamic map data provision system for automated vehicle. The Journal of the Korea Institute of Intelligent Transport Systems, 16(6), 208–218.CrossRef Yang, I., Jeon, W. H., & Lee, H. M. (2017). A study on dynamic map data provision system for automated vehicle. The Journal of the Korea Institute of Intelligent Transport Systems, 16(6), 208–218.CrossRef
Zurück zum Zitat Yi, B., Gottschling, S., Ferdinand, J., Simm, N., Bonarens, F., & Stiller, C. (2016). Real time integrated vehicle dynamics control and trajectory planning with MPC for critical maneuvers. In 2016 IEEE intelligent vehicles symposium (IV), 584–589. Yi, B., Gottschling, S., Ferdinand, J., Simm, N., Bonarens, F., & Stiller, C. (2016). Real time integrated vehicle dynamics control and trajectory planning with MPC for critical maneuvers. In 2016 IEEE intelligent vehicles symposium (IV), 584–589.
Zurück zum Zitat Zhang, Z., Knauder, B., Ackerl, M., & Pell, J. (2020). Validation of Road-Preview-Based Predictive Gear Selection on Heavy-Duty Vehicle Transmission Control Unit (No. 2020–01–0962). SAE Technical Paper. Zhang, Z., Knauder, B., Ackerl, M., & Pell, J. (2020). Validation of Road-Preview-Based Predictive Gear Selection on Heavy-Duty Vehicle Transmission Control Unit (No. 2020–01–0962). SAE Technical Paper.
Zurück zum Zitat Zhao, R. C., Wong, P. K., Xie, Z. C., & Zhao, J. (2017). Real-time weighted multi-objective model predictive controller for adaptive cruise control systems. International Journal of Automotive Technology, 18(2), 279–292.CrossRef Zhao, R. C., Wong, P. K., Xie, Z. C., & Zhao, J. (2017). Real-time weighted multi-objective model predictive controller for adaptive cruise control systems. International Journal of Automotive Technology, 18(2), 279–292.CrossRef
Metadaten
Titel
MPC Energy Prediction Control Simulation of a Hybrid Electric Vehicle
verfasst von
Jinkyeom Cho
Hyeongcheol Lee
Publikationsdatum
27.11.2024
Verlag
The Korean Society of Automotive Engineers
Erschienen in
International Journal of Automotive Technology
Print ISSN: 1229-9138
Elektronische ISSN: 1976-3832
DOI
https://doi.org/10.1007/s12239-024-00184-7