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Gasoline particulate filters (GPF) are becoming a standard technology in gasoline engines because of the need for compliance with particulate matter (PM) emissions requirement. Generally, GPFs can be placed after a three-way catalysts (TWC) in the same can, or in a separate can downstream. As typical wall-flow filters, particulate matter is removed from the exhaust by physical filtration using a honeycomb structure similar to an emissions catalyst substrate but with the channels blocked at alternate ends. The goal of work was to the study the filtration efficiency and regeneration capacity of the GPF. Laboratory emission tests were carried out for one 2.0L gasoline turbo direct injection (GTDI) prototype vehicle according to the new World Harmonized Light Vehicle Test Cycle (WLTC). The data showed that the vehicle has a reliable and high GPF filtration efficiency to intercept the particulate pollution from the exhaust. Meanwhile, five 2.0L GTDI prototype cars from respective China stage 6 platforms were used for further study of soot accumulation and regeneration capacity. The results, in terms of modeled emissions in tests under real driving conditions of China cities (Nanjing and Hainan), showed that the heavy traffic road conditions lead to a low probability of soot regeneration. However, the GPF regeneration capacity of the test convoy was still adequate. In addition, the drive cycle exhibiting good road conditions with more aggressive driving behaviors offered a better regeneration environment due to the elevated GPF temperature and more frequent occurrence of deceleration fuel shut off (DFSO) creating an environment of excess oxygen content.

During cold-starts, diesel engines equipped with aftertreatment systems typically use combustion phasing retard to increase exhaust gas enthalpy to hasten catalyst light-off, resulting in lower tailpipe emissions. Although later combustion phasing can help achieve faster catalyst light-off, combustion variability increases which can physically manifest as vibration and erratic engine behavior. To achieve faster catalyst light-off while remaining within combustion variability constraints, the premise of closed-loop control of Coefficient of Variation of IMEP (COVIMEP) to a target value using feedback from an in-cylinder pressure sensor has been explored. COVIMEP controllers have been designed using a model and validated via simulation and experiment at steady-state. The simulation and experimental results indicate that closed-loop COVIMEP control is a viable technique for retarding combustion phasing to the combustion variability limit at steady-state conditions.

In this paper, the development of a control-oriented piston temperature model for diesel engines is discussed. Using the underlying energy balance at the piston, a one-state piston temperature model was developed based on a thermal resistance concept. The model is composed of five sub-models: an engine model, a heat distribution model, a piston temperature model, an initial piston temperature model, and a maximum piston temperature model. In the engine model, the combustion heat transferred to the engine is calculated based on the energy balance in the cylinder chamber. The heat distribution model, which is a main feature in this model, determines the heat transferred to the piston using two maps as a function of engine speed and fuel depending on the piston cooling jet (PCJ) operation. The energy balance at the piston is applied to calculate the mean piston temperature, and the initial piston temperature is determined by the arbitration between the piston and the oil temperatures. The maximum piston temperature is estimated using a simple linear correction to the mean piston temperature. Integrating all sub-models in the Simulink platform, the model was identified and validated using piston temperature measurements under steady-state fuel steps as well as transient tests. There is a good agreement between the modeled and the measured piston temperatures with less than 4.1°C of root-mean-square-error (RMSE) over transient emissions cycles (FTP-75, LA92, and HWEFT). The modeled piston temperature can be used as an input to the control strategy of variable cooling devices, such as a variable displacement oil pump.

Predictive models of engine-out NOx emissions continue to be a topic of active research in the diesel powertrain community. Renewed interest in the use of in-cylinder pressure sensor has presented ...

A real-time implementable, zero-dimensional model for predicting engine-out emissions of nitrogen oxides using in-cylinder pressure measurements is developed. The model is an extension of existing works in open literature that align well with the objectives of real-time implementation. The proposed model uses a simplified Zeldovich NOx mechanism that uses combustion-related parameters derived from simplified thermodynamic and combustion sub-models. The performance of the model is discussed for both a heavy-duty and a light-duty diesel engines. The model behavior is evaluated under input uncertainty so as to provide realistic performance bounds.

Diesel engine emission cycle data shows that major portions of cycle emissions are produced at the beginning of the test, when the aftertreatment is not at operational temperature (prior to “light-off”) [1]. To reduce diesel emissions, aggressive combustion phasing retard via injection timing can be used to achieve faster aftertreatment light-off, but this method is limited because of vibration and harshness concerns associated with the combustion variability induced by the late combustion phasing. In order to achieve aggressive exhaust heating while mitigating combustion variability concerns, the premise of controlling combustion variability is explored. In particular, a controller will use real-time measurements of combustion features and control injection timing to maintain an acceptable level of combustion variability. The closed loop controller tuning requires an understanding of combustion variability behavior as a function of combustion phasing retard. The characterization of combustion variability using engine experiments is presented, and the findings are used to develop a control-oriented combustion variability model consisting of regressions of the statistics of IMEP as a function of fuel and timing offsets.

Combustion phasing retard is commonly used on diesel engines to achieve faster aftertreatment light-off and lower tailpipe emissions. Aggressive combustion phasing retard can achieve higher exhaust gas enthalpy at the cost of increased combustion variability, which can create vehicle noise, vibration, and harshness (NVH) issues. To avoid such issues while maximising exhaust heating, feedback from cylinder pressure sensors can be used to control the coefficient of variation of the indicated mean effective pressure (CoVIMEP) to a maximum allowable value. Therefore, a control-oriented combustion model that captures the stochastic properties of the cycle-to-cycle variability for IMEP has been developed for control design. Unbiased estimation methods for the CoVIMEP using finite impulse response (FIR) and infinite impulse response (IIR) filters are discussed. Finally, the performance of the estimation strategy is tested during an engine warm-up phase to show that it is a suitable alternative for generating a feedback signal for control.