Dissertation Defense: Biodiesel Accommodations in Both Conventional and Hybrid Electric Powertrains

Committee:

• Dr. Junmin Wang, Chair (ME)
• Dr. Chia-Hsiang Menq (ME)
• Dr. Ahmet Selamet (ME)
• Dr. Vishnu Baba Sundaresan (ME)

Abstract:

This dissertation investigated biodiesel’s accommodations in both conventional diesel engines and diesel-electric hybrid powertrains. To facility fuel adaptive control, two types of on board biodiesel blend level estimation strategies were proposed. Firstly, a steady-state fuel property estimator was designed by utilizing the information of fuel-dependent rail natural frequency, which can be extracted from the measurement of common rail pressure sensor. The difference of rail natural frequencies of diesel, biodiesel, gasoline, and ethanol were compared. And the results showed that the differences can be used for fuel type identification purpose. Secondly, in order to continuously monitor actual exhaust gas recirculation (EGR) levels while considering fuel property variation, a dynamic estimation strategy was proposed. An oxygen fraction dynamic model was developed for the engine with a dual-loop EGR system. Based on the model, an adaptive observer is designed for the joint estimation of air-path oxygen fractions and biodiesel blend level. With the blend level estimation, fuel adaptive control can be conducted to optimize engine performance and emission level. And a physics-based multi-phase combustion model was developed to predict ignition delay and CA50 for both diesel and biodiesel. And this model could be beneficial for fuel adaptive feedback control. As many fuel adaptive control strategies in conventional powertrain have been proposed in literature, only a brief review was provided. And in this dissertation, the efforts were further extended to study biodiesel’s influence on hybrid electric vehicle (HEV) powertrain coupled with diesel aftertreatment systems. A control-oriented model was developed by systematically incorporating of HEV models and aftertreatment thermal dynamics models. The model was able to predict engine-out temperature and emissions, and to simulate the temperature dynamics in the aftertreatment systems. A novel aftertreatment system warm-up strategy featured by applying both early and late post injections was developed. Fuel properties’ impact on post injections were also studied through experimental results. A supervisory controller was designed to optimize the post injection ratio as well as the torque split ratio of the HEV powertrain. With this approach, the warm-up time of aftertreatment systems can be significantly reduced and the SCR catalyst temperature can be kept within the desired range so that high emission reduction efficiency can be achieved. And this method was also compatible with biodiesel at a higher fuel cost compared to diesel.