Multidimensional modelling of Diesel Particulate Filter for regeneration control strategies

摘要

Control of Diesel Particulate Filter regenerations is becoming a key feature for car manufacturers, since even a low cracking of the DPF might lead to overshoot the Euro5+ regulations concerning soot emission. Strategies to protect the DPF are built for the most critical DPF regeneration conditions, the so-called "Back to Idle" tests. The development of those protection strategies is timeconsuming, since it requires many tests and then a lot of soot loading and regeneration steps. Moreover, tests are required to be very repeatable, since the strategy is chosen by comparing those tests between them. A high repeatability is very hard to get in real conditions. For example, slight changes of distribution and reactivity of soot can affect regeneration results. In the following study, we propose to replace those tests by using a methodology coupling real bench tests and simulation results. We used both experiments on a Diesel vehicle with empty DPF and a multi-1D DPF regeneration model to choose the worse "Back to Idle" scenario among up than 20 tests. Then we used the simulation tool to test several engine-tuning strategies in order to decrease the maximum internal DPF temperature in this scenario.