Modeling and control methods for improving drivability, power management and fuel economy in a hybrid electric vehicle

Enormous efforts and resources in research communities are focused on developing advanced energy management control systems to achieve improved fuel economy in power-split hybrid electric vehicles (HEVs). However, more research needs to be performed to improve other important attributes of HEVs as well. This research addresses other key attributes of power-split HEV as well, such as drivability, power management together with fuel economy improvement.; In this research, we first develop a complete power-split powertrain HEV model to study, analyze, design and evaluate control systems to improve attributes in a power-split HEV. The simulation and experimental vehicle tests validate the developed model and predicts the powertrain response with reasonable accuracy, and has a relatively high degree of fidelity.; Next we designed a novel controller to address a key attribute of drivability in a power-split HEV. Due to the characteristics of power-split configuration, it is very susceptible to sustained driveline oscillations. We presented the analysis on the root cause of sustained driveline resonance in power-split HEVs using both simulation and experimental tests. The designed active damping control system to address this issue in power-split HEVs for improving drivability was tested and validated for robustness under both simulation environment and experimental test vehicle.; We also present a novel approach, the first in the automotive field to implementing the rule-based fuzzy gain-scheduling PI controller to control desired engine power, engine speed and HV battery maintenance power behavior in the power-split HEV, which can improve two key attributes: drivability and HV battery power management. This control system's effectiveness was verified through simulations and experimental vehicle testing. In addition, to improve HV battery power management, we also developed an intelligent fuzzy logic based control system, again a first in the applied automotive field, that can minimize the HV battery power limits violations and hence can improve power management by enhancing HV battery life and reduce HV battery degradation. This fuzzy control system was evaluated under both simulation environment and real world HEV testing demonstrating the capability of improving power control or minimizing HV battery power limits violation.; Finally to improve the key attribute of fuel economy, we proposed an approach very different from optimization of energy management in HEVs, where we designed an advanced fuzzy rule-based driver advisory control system to provide feedback to the driver for improving fuel efficiency without significantly affecting the drivability in HEV. The simulation results and the testing in the experimental vehicle verified that the controller is capable of improving fuel economy in a HEV.