Approximate dynamic programming solution for the optimal nitrogen oxides/particulate matter trade-off control of a WAPS engine

Approximate dynamic programming is an effective optimal control method. This article researches a data-driven approximate dynamic programming. The method is extended to a nonlinear multi-input multi-output form. Using the data from a unique 4JB1-T weifu accumulator pump system (WAPS) engine, the developed approximate dynamic programming controller is trained to achieve its optimal trade-off emission control between the nitrogen oxides and particulate matter. The convergent proof of this method is given. The second-order training algorithm is introduced to promote the robust and convergent performance. The control objective is to let the WAPS engine pass the China State-IV emission test under the New European Drive Cycle. The bench test shows that an excellent control transient performance and significant promotion have been achieved. This article presents a new approach for the engine control and calibration. In addition, it also adds another dimension to the existing literature on the data-driven nonlinear multi-input multi-output trade-off emission control of the WAPS engine.

Abstract licence: CC BY

32 more references, whose wording the paper’s licence keeps private.

A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.