Erica Klampfl, Jenny Lee, David Dronzkowski, Kacie Theisen


Before an engine can be scheduled in the Product Development cycle for inclusion in a vehicle, it must be calibrated in such a way that it satisfies a variety of regulatory tests over a range of conditions. The current engine calibration process involves conducting a design of experiments at a representative number of steady state points in order to satisfy all required regulatory tests: test engineers use a standard 16×16 grid with standard grid spacing and then conduct a design of experiments on a subset of those points - about 120 of them. This work explores how to reduce the engine calibration process time by finding the best 16×16 grid choice (i.e. the best spacing on both the engine speed and torque axes) and the minimum number of points on the grid to test in order to satisfy regulatory constraints around NOX , particulate matter, noise, and fuel consumption. Our proposed method models the problem as a Binary Integer Program that simultaneously selects the best grid spacing and optimized number of points to test, while guaranteeing that all specified constraints hold. We present an example that demonstrates how we can reduce the number of necessary test points by approximately 56%.


  1. Balas, E. and Padberg, M. (1972). On the set coverying problem. Operations Research, 20:1152-1161.
  2. Castagné, M., Bentolila, Y., Chaudoye, F., Hallé, A., Nicolas, F., and Sinoquet, D. (2008). Comparison of engine calibration methods based on design of experiments (DoE). Oil & Gas Science and Technology, 63:563- 582.
  3. EPA (1977). Title 40 - protection of environment, CFR § 86 subpart B.
  4. Geoffrion, A. (1976). A guided tour of recent practical advances in integer linear programming. OMEGA, The international Journal of Management Science, 4(1):49-57.
  5. IBM (2010). IBM ILOG CPLEX optimization studio (OPL). http://www01.ibm.com/software/integration/optimization/cplexoptimization-studio/.
  6. Langouët, H., Métivier, L., Sinoquet, D., and Tran, Q. (2008). Optimization for engine calibration. In EngOpt 2008 - International Conference on Engineering Optimization. Rio de Janeiro, Brazil.
  7. Maloney, P. (2009). Objective determination of minimum engine mapping requirements for optimal SI DIVCP engine calibration. Warrendale: SAE International.
  8. Wolsey, L. (1998). Integer Programming. John Wiley & Sons, Inc.
  9. Yoshida, S., Ehara, M., and Koroda, Y. (2011). Rapid boundary detection for model-based diesel engine calibration. Warrendale: SAE International.

Paper Citation

in Harvard Style

Klampfl E., Lee J., Dronzkowski D. and Theisen K. (2012). ENGINE CALIBRATION PROCESS OPTIMIZATION . In Proceedings of the 1st International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES, ISBN 978-989-8425-97-3, pages 335-341. DOI: 10.5220/0003695603350341

in Bibtex Style

author={Erica Klampfl and Jenny Lee and David Dronzkowski and Kacie Theisen},
booktitle={Proceedings of the 1st International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES,},

in EndNote Style

JO - Proceedings of the 1st International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES,
SN - 978-989-8425-97-3
AU - Klampfl E.
AU - Lee J.
AU - Dronzkowski D.
AU - Theisen K.
PY - 2012
SP - 335
EP - 341
DO - 10.5220/0003695603350341