Browse Publications Technical Papers 2022-01-0553
2022-03-29

OBD Limit Part Creation Using DFSS Methodology: NMHC Catalyst Emissions Control System 2022-01-0553

In the light duty diesel segment, the need persists for an advanced control system to monitor the health of an aftertreatment system throughout a vehicle’s life in order to maintain compliance with ever tightening emissions levels. In on-board diagnostics (OBD), every diagnostic is validated during development stages to detect when a system under monitoring of that diagnostic has failed. This necessitates the need to create parts which represent a failure that would be observed on the vehicle. These failed parts, referred to as limit or threshold parts, are developed through a limit part creation process. Although there are commonalities amongst Original Equipment Manufacturers (OEM), each OEM has their own detection logic which will require a unique and specific limit part. Various methods exist for creating these limit parts, and each method produces a different combination of ability to detect the failure and its associated tailpipe emissions.
Historically for the OBD group within FCA, the Diesel Oxidation Catalyst (DOC) limit part has been created by a combination of reducing the catalyst volume and aging. To fully understand the effect of various combinations of volume reduction and aging of DOC and Diesel Particulate Filter (DPF) on the tailpipe emissions and its corresponding OBD diagnostic, a Design of Experiments (DOE) approach was implemented as part of a Design for Six Sigma (DFSS) project. This DOE laid out an array of 18 parts, and these parts were tested under two unique urban and highway test cycles and evaluated under the criteria of detectability and tailpipe emissions.
When evaluating the results, it became clear which limit parts were the appropriate choices that would work on a specific vehicle application. This method removes the trial and error approach for identifying an emissions control system limit part, and by replacing it with a statistically-based methodology, it significantly reduces the number of iterations needed during the development of OBD diagnostics.

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