Study On The Recognition Analysis Of Performance Degradation And Optimization Of The Diesel Particulate Filter

With the rapid increase of car ownership,the impact of automobile emission pollutants on the environment become more and more serious,and research about the vehicle emissions control has become a hotspot issue for urgent attention.Since more and more stringent emission standards and regulations have been gradually imple-mented,Particulate matter(PM)emission has become one of the key problems in the development of high efficiency and low emission diesel engine,which needs to be solved urgently.Currently,the wall-flow diesel particulate filter(DPF)is considered to be one of the most effective aftertreatment device for PM abatement in diesel powered vehicles.However,widely application of the DPF in automobiles is re-stricted due to its performance deterioration and failure after multiple regenerations in harsh working conditions(such as high temperature,thermal shock and ash deposition)in the porous media filter,and DPF degradation can inevitably result in the increase of pressure drop as well as the decrease of filtration efficiency and regeneration effi-ciency,limiting the DPF's in use service life,so that the DPF requires removal for periodic cleaning or replacement.Therefore,it is quite necessary to carry out the in-vestigation on the recognition analysis of performance degradation and optimization of the diesel particulate filter by the numerical simulation and experiment,combined with relevant theory and algorithm in this paper.The research results not only provide a theoretical basis for the design and application of the diesel particulate filter,but also have important theoretical and practical significance to improve the comprehen-sive performance of the diesel particulate filter and control the environmental pollu-tion.The main research work of this paper is as follows:(1)Considering the effect of ash deposition on the DPF performances,a compo-site regeneration model is established on the DPF using a new composite regeneration mode by coupling microwave and ceria-manganese base catalytic additive(MnOx-CeO2)in diesel fuel,and it is verified by tests,which provides theoretical support for the influence factors analysis of the performance degradation and multi-disciplinary design optimization of the DPF.(2)A method for evaluation of the influence of various factors on DPF's per-formance degradation is proposed;orthogonal experimental design(OED)is used to reduce the number of cases and save computational time;the maximum wall temper-ature and the pressure drop are taken as the evaluation indexes of thermal aging and filter clogging of the DPF,respectively,and they are calculated by the composite re-generation mathematical model for each case;finally,fuzzy grey relational analysis(FGRA)combined with fuzzy analytic hierarchy process'(FAHP)is employed to comprehensively evaluate the impacts of various factors on performance deterioration of the DPF.(3)Taking ash deposition mass and pressure drop as time series,they are pre-dicted according to their own characteristics based on combination forecasting meth-od such as the fuzzy adaptive variable weight method and a combination model of grey model and covering algorithm based on quotient space granular computing the-ory,respectively.The results show that the prediction models have high prediction precision,which can provide analysis data for DPF's failure recognition.(4)Failure cusp catastrophe model of a porous medium filter in DPF is estab-lished using catastrophe theory and diffeomorphism transformation based on the pressure drop model of a porous medium filter with ash deposition.Then,critical points and singular points of the failure cusp catastrophe model are solved and the discriminant of the DPF failure cusp catastrophic model is obtained,which is used to recognize the failure behaviour of the DPF.Finally,failure or critical state details of DPF are acquired via calculation examples,and recognition results of the DPF failure behaviour are verified on the engine bench test.Recognition results of the failure state are consistent with the experimental ones,which confirms the validity of failure recognition based on the failure cusp catastrophe model of the DPF.(5)Taking pressure drop,regeneration performance,microwave energy con-sumption,and thermal shock resistance as the objective functions,a multidisciplinary design optimization(MDO)model of the DPF is established based on the multidisci-plinary design optimization theory.Then,the DPF is optimized by using MDO method based on adaptive mutative scale chaos optimization algorithm.Finally,op-timized results are verified by experiments,and the performance comparisons of the original DPF and the optimized DPF are summarized.