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Technical Paper

Development of Emission Transfer Functions for Predicting the Deterioration of a Cu-Zeolite SCR Catalyst

2009-04-20
2009-01-1282
Urea selective catalytic reduction (SCR) catalysts have the capability to deliver the high NOx conversion efficiencies required for future emission standards. However, the potential for the occasional over-temperature can lead to the irreversible deactivation of the SCR catalyst. On-board diagnostics (OBD) compliance requires monitoring of the SCR function to make sure it is operating properly. Initially, SCR catalyst performance metrics such as NOx conversion, NH3 oxidation, NH3 storage capacity, and BET surface area are within normal limits. However, these features degrade with high temperature aging. In this work, a laboratory flow reactor was utilized to determine the impact on these performance metrics as a function of aging condition. Upon the completion of a full time-at-temperature durability study, four performance criteria were established to help determine a likely SCR failure.
Journal Article

Smart DPF Regenerations - A Case Study of a Connected Powertrain Function

2019-04-02
2019-01-0316
The availability of connectivity and autonomy enabled resources, within the automotive sector, has primarily been considered for driver assist technologies and for extending the levels of vehicle autonomy. It is not a stretch to imagine that the additional information, available from connectivity and autonomy, may also be useful in further improving powertrain functions. Critical powertrain subsystems that must operate with limited or uncertain knowledge of their environment stand to benefit from such new information sources. Unfortunately, the adoption of this new information resource has been slow within the powertrain community and has typically been limited to the obvious problem choices such as battery charge management for electric vehicles and efforts related to fuel economy benefits from adaptive/coordinated cruise control. In this paper we discuss the application of connectivity resources in the management of an aftertreatment sub-system, the Diesel Particulate Filter (DPF).
Journal Article

Machine Learning Approach for Constructing Wet Clutch Torque Transfer Function

2021-04-06
2021-01-0712
A wet clutch is an established component in a conventional powertrain. It also finds a new role in electrified systems. For example, a wet clutch is utilized to couple or decouple an internal combustion engine from an electrically-driven drivetrain on demand in hybrid electric vehicles. In some electrical vehicle designs, it provides a means for motor speed reduction. Wet clutch control for those new applications may differ significantly from conventional strategy. For example, actuator pressure may be heavily modulated, causing the clutch to exhibit pronounced hysteresis. The clutch may be required to operate at a very high slip speed for unforeseen behaviors. A linear transfer function is commonly utilized for clutch control in automating shifting applications, assuming that clutch torque is proportional to actuator pressure. However, the linear model becomes inadequate for enabling robust control when the clutch behavior becomes highly nonlinear with hysteresis.
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