Contribution of High Accuracy Temperature Sensors Towards Fuel Economy and Robust Calibration 2014-01-1548
Tighter emission limits are discussed and established around the world to improve quality of the air we breathe. In order to control global warming, authorities ask for lower CO2 emissions from combustion engines. Lots of efforts are done to reduce engine out emissions and/or reduce remaining by suitable after treatment systems.
Watlow, among others, a manufacturer of high accurate, active temperature sensor ExactSense™, wanted to understand if temperature sensor accuracy can have an influence on fuel consumption (FC). For this purpose a numerical approach was chosen where several non-road driving cycles (NRTCs) were simulated with the data base of a typical Stage IV heavy duty diesel engine. The engine is equipped with an exhaust gas after treatment system consisting of a DOC, CDPF and an SCR. In this work scope, the investigations shall be restricted to the FC benefits obtained in the active and passive DPF regeneration. The numerical investigations were performed using DPF soot loading and oxidation models using a commercially available software program.
The passive regeneration by NO2 oxidation (CRT effect) and the active regeneration by O2 oxidation are modeled using the temperature sensors installed upstream and downstream DOC, along with other signals as inputs. The modeled soot load was used to trigger the activation and deactivation of the heat mode for active regeneration. The models used to calculate NO2 formation over the DOC and the CDPF, as well as those used for NO2 and O2 oxidation in the CDPF are comparable to commonly used models in engine control units (ECUs).
Temperature sensor tolerances show significant influences on active regeneration durations, resulting in noticeable fuel savings benefit for high accuracy temperature sensors in the NRTC. Depending on the regeneration intervals and therefore depending on the application this potential might be considerable. Further it has been shown that high accuracies in temperature measurement lead to a more robust model calibration.