Driving Cycle Equivalence and Transformation

Abstract

There is a strong trend to use driving cycles extensively in vehicle design, particularly for the calibration and tuning of all powertrain systems for control and diagnosis. In such situations, it is essential to capture real driving; therefore, using only a few driving cycles would lead to the risk that a test or a design is tailored to a specific driving cycle. Consequently, there are now widespread activities using techniques from statistics, big data, and mission modeling to address these issues. For all such methods, there is an important final step to calibrate a representative cycle to adhere to fair propulsion requirements on the driven wheels over a cycle. For this, a general methodology has been developed, which is applicable to a wide range of problems involving driving cycle transformations. It is based on a definition of equivalence for driving cycles of, loosely speaking, being similar without being the same. Based on this definition, a set of algorithms is developed to transform a given driving cycle into an equivalent driving cycle or into a cycle with a given equivalence measure. The transformations are effectively handled as a nonlinear program that is solved by using general-purpose optimization techniques. The proposed method is general, and a wide range of constraints can be used.