Skip to main content
SpringerLink
Log in

Chances and Challenges in Automotive Predictive Control

  • Chapter
Automotive Model Predictive Control

Part of the book series: Lecture Notes in Control and Information Sciences ((LNCIS,volume 402))

Abstract

Recent years have witnessed an increased interest in model predictive control (MPC) for fast applications. At the same time, requirements on engines and vehicles in terms of emissions, consumption and safety have experienced a similar increase. MPC seems a suitable method to exploit the potentials of modern concepts and to fulfill the automotive requirements since most of them can be stated in the form of a constrained multi input multi output optimal control problem and MPC provides an approximate solution of this class of problems. In this introductory chapter, we analyze the rationale, the chances and the challenges of this approach. This chapter does not intend to review all the literature, but to give a flavor of the challenges and chances offered by this approach.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 139.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 179.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Alamir, M.: Stabilization of Nonlinear System Using Receding-Horizon Control Schemes: A parametrized approach for Fast Systems. LNCIS. Springer, London (2006)

    Google Scholar 

  2. Alamir, M., Sheibat-Othman, N., Othman, S.: Constrained nonlinear predictive control for maximizing production in polymerization processes. IEEE Transactions on Control Systems Technology 15, 315–323 (2007)

    Article  Google Scholar 

  3. Alberer, D., del Re, L.: Optimization of the transient diesel engine operation. In: Proceedings of the 9th International Conference on Engines and Vehicles, Capri, Naples, Italy (2009)

    Google Scholar 

  4. Alberer, D., del Re, L., Winkler, S., Langthaler, P.: Virtual sensor design of particulate and nitric oxide emissions in a DI diesel engine. In: Proceedings of the ICE 2005, 7th International Conference on Engines for Automobile, Capri, Italy (September 2005)

    Google Scholar 

  5. Ammann, M., Fekete, N.P., Guzzella, L., Glattfeder, A.H.: Model based control of the VGT and EGR in turbocharged common-rail diesel engine: Theory and passenger car implementation. SAE Transactions 112, 527–538 (2003)

    Google Scholar 

  6. Bemporad, A., Giorgetti, N., Kolmanovsky, I.V., Hrovat, D.: A hybrid system approach to modeling and optimal control of DISC engines. In: 41th IEEE Conf. on Decision and Control, pp. 1582–1587 (2002)

    Google Scholar 

  7. Bemporad, A., Morari, M., Dua, V., Pistikopoulos, E.N.: The explicit linear quadratic regulator for constrained systems. Automatica 38, 3–20 (2002)

    Article  MATH  MathSciNet  Google Scholar 

  8. Borrelli, F., et al.: An MPC/hybrid system approach to traction control. IEEE Trans. Contr. Systems Technology 14(3), 541–552 (2006)

    Article  Google Scholar 

  9. Corona, D., Necoara, I., De Schutter, B., van den Boom, T.: Robust hybrid MPC applied to the design of an adaptive cruise controller for a road vehicle, San Diego, California, pp. 1721–1726 (2006)

    Google Scholar 

  10. Alberer, D., Kirchsteiger, H., del Re, L., Ferreau, H.J., Diehl, M.: Receding horizon optimal control of wiener systems by application of an asymmetric cost function. In: IFAC Workshop on Control Applications of Optimisation, Jyväskylä, Finnland, May 6-8 (2009)

    Google Scholar 

  11. Lichtenthäler, D., Ayeb, M., Theuerkauf, H.J., Winsel, T.: Improving real-time SI engine models by integration of neural approximators, SAE Technical Paper Series, Paper No. 1999-01-1164 (1999)

    Google Scholar 

  12. del Re, L.: Hybrid MPC for minimum phase nonlinear plants. In: Tagungsband Third European Control Conference (1995)

    Google Scholar 

  13. Devasia, S.: Should model-based inverse inputs be used as feedforward under plant uncertainty? IEEE Transactions on Automatic Control 47(11), 1865–1871 (2002)

    Article  MathSciNet  Google Scholar 

  14. Diehl, M., Bock, H.B., Schlöder, J.P.: A real-time iteration scheme for nonlinear optimization in optimal feedback control. Siam Journal on Control and Optimization 43, 1714–1736 (2005)

    Article  MATH  MathSciNet  Google Scholar 

  15. Stölting, E., Seebode, J., Gratzke, R., Behnk, K.: Emissionsgeführtes motormanagement für nutzfahrzeuganwendungen. In: MTZ December (2008)

    Google Scholar 

  16. Falcone, P., Borelli, F., Asgari, J., Tseng, H.E., Hrovat, D.: Predictive active steering control for autonomous vehicle systems. IEEE Transactions on Control Systems Technology 15 (2007)

    Google Scholar 

  17. Falcone, P., Borelli, F., Asgari, J., He, T., Hrovat, D.: A model predictive control approach for combined braking and steering in autonomous vehicles. In: Proceedings of the IEEE Conference on Control and Automation (2007)

    Google Scholar 

  18. Falcone, P., de Gennaro, M.C., Fiengo, G., Glielmo, L., Santini, S., Langthaler, P.: Torque generation model for diesel engine. In: 42nd IEEE Conference on Decision and Control, Hawaii, USA, December 2003, pp. 1771–1776 (2003)

    Google Scholar 

  19. Ferreau, H.J., Bock, H.G., Diehl, M.: An online active set strategy for fast solution of parametric quadratic programs with applications to predictive engine control. Diploma Thesis, University of Heidelberg (2006)

    Google Scholar 

  20. Findeisen, R., Algöwer, F.: An introduction to nonlinear model predictive control. In: 21st Benelux Meeting on Systems and Control (2002)

    Google Scholar 

  21. Wang, G., Li, G., Liu, Y., Chen, L., Zhang, X., Lu, J.: A Developed Model for Emission Prediction. SAE Paper No. 1999-01-0233 (1999)

    Google Scholar 

  22. Garcia, C.E., Morshedi, A.M.: Quadratic programming solution of dynamic matrix control QDMC. Chemical Engineering Communications 46, 73–87 (1986)

    Article  Google Scholar 

  23. Heywood, J.: Internal Combustion Engine Fundamentals (1988)

    Google Scholar 

  24. Hirsch, M., Alberer, D., del Re, L.: Grey-box control oriented emissions models. In: 17th IFAC World Congress, Seoul, Korea (July 2008)

    Google Scholar 

  25. Hirsch, M., del Re, L.: Adapted D-optimal experimental design for transient emission models of diesel engines. In: Proceedings of the 9th International Conference on Engines and Vehicles, Capri, Naples, Italy (2009)

    Google Scholar 

  26. Hjalmarsson, H., Martensson, J.: Optimal input design for identification of non-linear systems: Learning from the linear case. In: Proceedings of the 2007 American Control Conference, New York City (July 2007)

    Google Scholar 

  27. Isidori, A.: Nonlinear Control Systems, 2nd edn. (1997)

    Google Scholar 

  28. Galindo, J., Luján, J.M., Serrano, J.R., Hernández, L.: Combustion simulation of turbocharger hsdi diesel engines during transient operation using neural networks. Applied Thermal Engineering 25, 877–898 (2005)

    Article  Google Scholar 

  29. Desantes, J.M., Lopez, J.J., Garcia, J.M., Hernandez, L.: Application of neural networks for prediction and optimization of exhaust emissions in a h.d. diesel engine. SAE-Paper No. 2002-01-1144 (2002)

    Google Scholar 

  30. Johansen, T.A.: Approximate explicit receding horizon control of constrained nonlinear systems. Automatica 40, 293–300 (2004)

    Article  MATH  MathSciNet  Google Scholar 

  31. Jung, M.: Mean-value modelling and robust constrol of the airpath of a turbocharged diesel engine. PhD Thesis,University of Cambridge (2003)

    Google Scholar 

  32. Klingenberg, H.: Automobile Exhaust Emission Testing. Springer, Heidelberg (1996)

    Google Scholar 

  33. Langthaler, P.: Model Predictive Control of a diesel engine airpath. PhD Thesis, Johannes Kepler Universität (2007)

    Google Scholar 

  34. Lazar, M., Heemels, W.P.M.H., Munoz de la Pena, D., Alamo, T.: Further results on Robust MPC using Linear Matrix Inequalities. In: Assessment and Future Directions of Nonlinear Model Predictive Control. LNCIS. Springer, Heidelberg (2009)

    Google Scholar 

  35. Li, X., Wallace, J.S.: A phenomenological model for soot formation and oxidation in direct-injection diesel engines. SAE Paper No. 952428 (1995)

    Google Scholar 

  36. Costa, M., Merola, S., and Vaglieco, B.M.: Mulitdimensional modelling and spectroscopic analysis of the soot formation process in a diesel engine. 2002-01-2161 (2002)

    Google Scholar 

  37. Hafner, M., Schüller, M., Nelles, O., Isermann, R.: Fast neural networks for diesel engine control design (2000)

    Google Scholar 

  38. Barbarisi, O., Palmieri, G., Scala, S., Glielmo, L.: European Journal of Control 15(3-4) (2009)

    Google Scholar 

  39. Ohtsuka, T.: A continuation/GMRES method for fast computation of nonlinear receding-horizon control. Automatica 40, 563–574 (2004)

    Article  MATH  MathSciNet  Google Scholar 

  40. Oppenauer, K., del Re, L.: Hybrid emission models. In: Proceedings of the 9th International Conference on Engines and Vehicles, Capri, Naples, Italy (2009)

    Google Scholar 

  41. Ortner, P., Bergmann, R., Ferreau, H.J., del Re, L.: Nonlinear model predictive control of a diesel engine airpath. In: IFAC Workshop on Control Applications of Optimisation, Agora, Finland (2009)

    Google Scholar 

  42. Ortner, P., del Re, L.: Predicitve control of a diesel engine air path. IEEE Transactions on Automatic Control 15, 449–456 (2007)

    Google Scholar 

  43. Previdi, F., Lovera, M.: Identification of non-linear parametrically varying models using separable least squares. International Journal of Control 77, 1382–1392 (2004)

    Article  MATH  MathSciNet  Google Scholar 

  44. Qin, S.J., Badgwell, T.A.: A survey of industrial model predictive control technology. Control Engineering Practice 11, 733–764 (2003)

    Article  Google Scholar 

  45. Rawlings, J.B.: Tutorial overview of model predictve control. IEEE Control Systems Magazine (2000)

    Google Scholar 

  46. Rückert, J., Richert, F., Schloßer, A., Abel, D., Herrmann, O.E., Pfeifer, A., Pischinger, S.: Ein modellgestützter prädiktiver ansatz zur regelung von ladedruck und agr-rate beim nutzfahrzeug-dieselmotor. In: Steuerung und Regelung von Fahrzeugen und Motoren - AUTOREG 2004, vol. 1828, pp. 131–141 (2004)

    Google Scholar 

  47. Lee, S., Shin, D., Lee, J., Sung, N.: Soot emission form a direct injection diesel engine. Paper No. 2004-01-0927 (2004)

    Google Scholar 

  48. Paoletti, S., Juloski, A.L., Ferrari-Trecate, G., Vidal, R.: Identification of hybrid systems: a tutorial. European Journal of Control 513(2-3), 242–260 (2007)

    Article  Google Scholar 

  49. Stewart, G., Borelli, F.: A model predictive control framework for industrial turbodiesel engine control. In: IEEE Conference on Decision and Control (2008)

    Google Scholar 

  50. Winsel, T., Ayeb, M., Lichtenthäler, D., Theuerkauf, H.J.: A neural estimator for cylinder pressure and engine torque. SAE Technical Paper Series, Paper No. 1999-01-1165 (1999)

    Google Scholar 

  51. Tennant, J.A., Rao, H.S., Powell, J.D.: Engine characterization and optimal control. In: IEEE Conference on Decision and Control including the Symposium on Adaptive Processes (1979)

    Google Scholar 

  52. Terwen, S., Back, M., Krebs, V.: Predictive powertrain control for heavy duty truck. In: Proceedings of the IFAC Symposium on Advances in Automotive Control, p. 39 (2004)

    Google Scholar 

  53. Tree, D., Svensson, K.I.: Soot processes in compression ignition engines. Progress in Energy and Combustion Science 33, 272–309 (2007)

    Article  Google Scholar 

  54. van Nieuwstadt, M.J., Moraal, P.E., Kolmanovsky, I.V., Stefanopoulou, A., Wood, P., Criddle, M.: Decentralized and multivariable designs for EGR-VGT control of a diesel engine. In: IFAC Workshop on Advances in Automotive Control, Mohican State Park, OH (1998)

    Google Scholar 

  55. Vasak, M., Baotic, M., Morari, M., Petrovic, I., Peric, N.: Constrained optimal control of an electronic throttle. International Journal of Control 79(5), 465–478 (2006)

    Article  MATH  MathSciNet  Google Scholar 

  56. Wei, X.: Advanced LPV techniques for diesel engines. PhD Thesis, Johannes Kepler Universität (2006)

    Google Scholar 

  57. Wei, X., del Re, L., Langthaler, P.: LPV dynamical models of diesel engine nox emission. In: First IFAC Symposium on Advances in Automotive Control, University of Salerno, Salerno, Italy, April 2004, pp. 262–267 (2004)

    Google Scholar 

  58. Wei, X., del Re, L., Lihua, L.: Air path identification of diesel engines by lpv techniques for gain scheduled control. Mathematical and Computer Modelling of Dynamical Systems 14(6), 495–513 (2008)

    Article  MATH  Google Scholar 

  59. Winkler, S., Hirsch, M., Affenzeller, M., del Re, L., Wagner, S.: Virtual sensors for emissions of a diesel engine produced by evolutionary system identification. In: Proceedings of the 12th International Conference on Computer Aided System Theory (2009)

    Google Scholar 

  60. Yu-Jia, Z., Ding-Li, Y.: A neural network model based MPC of engine AFR with single-dimensional optimization. In: Liu, D., Fei, S., Hou, Z.-G., Zhang, H., Sun, C. (eds.) ISNN 2007. LNCS, vol. 4491, pp. 339–348. Springer, Heidelberg (2007)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Institute for Design and Control of Mechatronical Systems, Johannes Kepler Universität Linz,  

    Luigi del Re, Peter Ortner & Daniel Alberer

Authors
  1. Luigi del Re
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Peter Ortner
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Daniel Alberer
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Institute for Design and Control of Mechatronical Systems, Johannes Kepler University Linz, Altenbergerstr. 69, 4040, Linz

    Luigi del Re

  2. Institute for Systems Theory and Automatic Control, University of Stuttgart, Pfaffenwaldring 9, 70550, Stuttgart

    Frank Allgöwer

  3. Facoltà di Ingegneria, Università del Sannio in Benevento, Corso Garibaldi 107, 82100, Benevento

    Luigi Glielmo

  4. Departamento de Máquinas y Motores Térmicos, Universidad Politécnica de Valencia (UPV), Camino de Vera, s/n., 46022, Valencia, (Spain)

    Carlos Guardiola

  5. Ford Research and Adv. Engineering, Ford Motor Company, Technical Leader, Powertrain Control R&A, 2101 Village Road Dearborn, 48124, MI

    Ilya Kolmanovsky

Rights and permissions

Reprints and permissions

Copyright information

© 2010 Springer London

About this chapter

Cite this chapter

del Re, L., Ortner, P., Alberer, D. (2010). Chances and Challenges in Automotive Predictive Control. In: del Re, L., Allgöwer, F., Glielmo, L., Guardiola, C., Kolmanovsky, I. (eds) Automotive Model Predictive Control. Lecture Notes in Control and Information Sciences, vol 402. Springer, London. https://doi.org/10.1007/978-1-84996-071-7_1

Download citation

  • DOI: https://doi.org/10.1007/978-1-84996-071-7_1

  • Publisher Name: Springer, London

  • Print ISBN: 978-1-84996-070-0

  • Online ISBN: 978-1-84996-071-7

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation