This article proposes a diesel oxidation catalyst diagnostics strategy based on the exothermic process generated by exhaust gas species oxidation in the catalyst. The diagnostics strategy is designed to be applied on-board and respecting real-time electronic control unit computational limitations. Diagnosis purposes are fulfilled by means of the comparison of the passive model temperature, which represents the outlet temperature of a non-impregnated diesel oxidation catalyst, and the measurement provided by the on-board catalyst-out temperature sensor. Thus, the presented diagnostics strategy uses only two production grade temperature sensors and the measurements of air and fuel mass flows from the electronic control unit. Passive diagnostics is based on the oxidation of engine-raw emissions, whilst active diagnostics is based on the oxidation of requested post injected fuel. Post-injection strategy is also discussed for active diagnosis. Then, the diagnostics strategy is able to discern whether the diesel oxidation catalyst is able to oxidise or not.

With the tightening of on-board diagnostics requirements, accuracy of sensors is essential to monitor the efficiency and ensure a proper control of the after-treatment systems. Temperature sensors are commonly used in the exhaust line at the diesel oxidation catalyst-inlet of turbocharged diesel engines for control and diagnosis of the after-treatment system. In particular, negative temperature constant sensors are used for this purpose. However, due to the necessary on-board robustness that sensors must fulfil, thermal inertia causes significant differences during engine transient operating conditions in temperature measurements. A Kalman filter is proposed in this paper for the on-line dynamic estimation of the catalyst-inlet temperature, which combines a slow but accurate measurement of the on-board temperature sensor with a fast but drifted temperature model. A fast research-grade thermocouple is used as reference of the actual exhaust gas temperature and a frequency analysis is performed in order to calibrate the model and analyse results of the signal reconstruction. Results of the algorithm are then successfully proved in experimental transient tests and typical European approval test cycles.

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Current diesel engine regulations include on-board diagnostic requirements so that after-treatment systems need on-board methods to detect their aging state through the available measurements. In a state-of-the-art diesel exhaust line, two temperature and [Formula: see text] measurements can be found upstream and downstream of the diesel oxidation catalyst. Thus, the strategy presented in this article makes use of these measurements to estimate the light-off temperature, which has been widely studied as a characteristic of diesel oxidation catalyst aging. The light-off temperature estimation potential is evaluated first under dynamic engine operating conditions, in which [Formula: see text] measurements are proved to be precise enough to detect oxidation. However, dynamic conditions make the association of a representative temperature with an oxidation event difficult. Therefore, the method makes use of more controlled conditions at idle, during which the exhaust temperature decreases avoiding dynamics of normal driving conditions. During the idle, post-injection pulses are applied to determine whether oxidation occurs at a representative temperature measured by the upstream temperature sensor. The result of each pulse is used to generate a database. Then, after a long enough time window, the database generated will allow characterizing non-oxidation and oxidation temperatures, with an intermediate interval of indefinition. This article shows how the temperatures of these ranges increase as the light-off temperature increases, thereby validating the proposed method for light-off temperature estimation.