Research On Early Warning Technology For Irregular Operation In Emission Testing Of Diesel Vehicles Under Lugdown Cycle

Accurate identification of high-emission vehicles is crucial for the implementation of automotive emission inspection and maintenance systems.Periodic emission inspection is the primary means of identifying high-emission vehicles,but currently,there is a persistent issue of Irregular inspections by emission inspection institutions.The regulatory methods employed by industry management department still heavily rely on manual processes,resulting in low regulatory effectiveness and difficulties in warning against Irregularity.In response to the aforementioned issues,this study integrates investigative research,theoretical analysis,and data analysis to explore the development of a warning system for detecting and alerting Irregular operations in diesel vehicle emission testing using the Lug-Down method.The primary research work and achievements are as follows:（1）A warning system for detecting Irregular operations was established,and methods for data preprocessing were investigated.An investigation and analysis were conducted on the regulatory standards,characteristics of Irregular operations,and the current state of industry management in diesel vehicle emission testing using the Lug-Down method.Considering the trends of government management simplification,scientific and information-based development,as well as the characteristics of industry regulation involving"online monitoring and warning"and"offline evidence collection and enforcement,"the objective was to provide clues for on-site enforcement by industry regulators and prioritize the strengthening of video and digital automatic warnings.Consequently,a diesel vehicle emission testing warning system was constructed,incorporating both online and offline approaches and combining automated and manual methods.In consideration of the data characteristics of the emission testing regulatory system,an analysis was conducted,and the boxplot method combined with dynamic gradient thresholding was selected as the approach for eliminating abnormal data.（2）The study focused on the warning technology for Irregular exhaust gas sampling operations.The characteristics of Irregular exhaust gas sampling operations were analyzed,and the feasibility of selecting CO₂ concentration as a parameter for warning against Irregular sampling operations was demonstrated.The impact of changes in diesel engine emission control technology routes and technological states on exhaust gas CO₂ concentration was analyzed,leading to the determination of a classification warning strategy that simultaneously considers the emission control technology routes and technological states of diesel engines.Through statistical analysis of the research samples,the graded threshold curve for warning against Irregular exhaust gas sampling operations was determined,and the corresponding warning results and response strategies were given.（3）The study focused on the warning technology for Irregular throttle control.The characteristics of Irregular driving operations during test conditions were analyzed,and Irregular throttle control was selected as the research priority.Through dynamic analysis of the vehicle during emission testing using the Lug-Down method on a chassis dynamometer,it was determined that the difference in wheel power between two 80%Vel Max HP points,namely the power dynamic scanning phase and the exhaust sampling stable operation phase,would serve as the parameter for warning against Irregular throttle control during the testing process.A warning model for the wheel power difference was established,taking into account the difference between steady-state and dynamic engine power and the rotational inertia of rotating components such as the vehicle’s driving wheels and engine flywheel.Through statistical analysis of the research samples,the graded threshold curves for warning against Irregular throttle control were derived for three different vehicle classes based on total mass,and the corresponding warning results and response strategies were given.（4）An alert system for detecting Irregular operations was designed and developed.The system primarily consists of four modules:communication connection,information transmission,warning,and result storage.It possesses key functionalities such as data communication,data extraction,data processing,Irregular operation identification,and result storage.The system was subjected to trial testing to validate its effectiveness in warning against Irregular operations in diesel vehicle emission testing using the Lug-Down method.