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This paper first presents a basic mean value engine plant model implemented in a hardware-in-the-loop (HIL) system. The plant model includes some basic engine parameters such as engine speed, manifold absolute pressure, etc., which are critical to both control algorithm integrity and default actions that result from improper signal performance (e.g., ECU shuts down due to corrupted signal(s)). The model is then improved to develop the HIL bench-based testing capabilities in the areas where a vehicle has traditionally been required. The on-board diagnostic monitor tests covered by SID $06 of SAE J1979 are selected as a case study. Specifically, for OBD exhaust gas sensor monitor testing purposes, the oxygen sensor model is developed to simulate normal or abnormal binary switching signals which might have asymmetric “lean to rich” and “rich to lean” transitions, or largely off maximum/minimum sensor voltages, etc.

This paper describes the verification and comparison of position control algorithms for a continuously-variable cam phaser. Robust Engineering techniques are used. Two non-linear PID control algorithms are designed to control cam phaser position. The first algorithm is a more complex control strategy while the second is a thrifted approach that seeks to reduce throughput requirements. An L18 orthogonal array is established with noise factors that affect the quality of cam phaser control. Using the orthogonal array, the number of experiment test points required to characterize the control algorithm response is reduced from 8,748 to thirty-six. The test points of the orthogonal array are investigated experimentally on a motored engine outfitted with cam phaser hardware. The desired and actual cam position data are compared and analyzed for all points in the orthogonal array.

A coolant temperature model of an internal combustion engine has been formulated to meet the new On-Board Diagnostics II (OBD II) requirement for coolant temperature rationality. The model utilizes information available within the production Engine Control Module (ECM). The temperature prediction capability has been tested for various “real-world” driving conditions and cycles along with regulated drive cycles. The model can be calibrated to find the appropriate timing for initiation of a diagnostic algorithm for engine cooling system and Coolant Temperature Sensor (CTS) faults. A diagnostic scheme has been developed to detect and isolate various types of cooling system failures using engine soak time information available from a low power timer in the ECM.

This paper describes the development of a vacuum-decay based evaporative leak detection sub-system that meets the model year 2000 California Air Resources Board (CARB) requirements.1 The diagnostic algorithm was developed and tested to create a production intent calibration. In addition, the calibration was validated during a four month test period of diagnostic and driveability performance, which included hot ambient, high volatility fuels, and altitude. It was found to detect 0.020 inch leaks reliably in-use, while being robust to misdiagnosis of smaller leaks.