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A hybrid electric vehicle simulation tool (HE-VESIM) has been developed at the Automotive Research Center of the University of Michigan to study the fuel economy potential of hybrid military/civilian trucks. In this paper, the fundamental architecture of the feed-forward parallel hybrid-electric vehicle system is described, together with dynamic equations and basic features of sub-system modules. Two vehicle-level power management control algorithms are assessed, a rule-based algorithm, which mainly explores engine efficiency in an intuitive manner, and a dynamic-programming optimization algorithm. Simulation results over the urban driving cycle demonstrate the potential of the selected hybrid system to significantly improve vehicle fuel economy, the improvement being greater when the dynamic-programming power management algorithm is applied.

Compared with conventional vehicles, electric vehicles (EVs) offer the benefits of replacing petroleum consumption and reducing air pollutions. However, there have been controversies over greenhouse gas (GHG) emissions of EVs from the life-cycle perspective in China’s coal-dominated power generation context. Besides, it is in doubt whether the cost-effectiveness of EVs in China exceeds other fuel-efficient vehicles considering the high prices. In this study, we compared the life-cycle GHG emissions of existing vehicle models in the market. Afterwards, a cost model is established to compare the total costs of vehicles. Finally, the cost-effectiveness of different vehicle types are compared. It is concluded that the GHG emission intensity of EVs is lower than reference and hybrid vehicles currently and is expected to decrease with the improvement of the power grid.

This study investigates the impact of transient engine operation on the emissions formed during a tip-in procedure. A medium-duty production V-8 diesel engine is used to conduct experiments in which the rate of pedal position change is varied. Highly-dynamic emissions instrumentation is implemented to provide real-time measurement of NOx and particulate. Engine subsystems are analyzed to understand their role in emissions formation. As the rate of pedal position change increases, the emissions of NOx and particulates are affected dramatically. An instantaneous load increase was found to produce peak NOx values 1.8 times higher and peak particulate concentrations an order of magnitude above levels corresponding to a five-second ramp-up. The results provide insight into relationship between driver aggressiveness and diesel emissions applicable to development of drive-by-wire systems. In addition, they provide direct guidance for devising low-emission strategies for hybrid vehicles.

An early-design methodology for predicting both expected fuel economy and catalyst-out CO, HC and NOx concentrations during arbitrarily-defined transient cycles is presented. The methodology is based on utilizing a vehicle-powertrain model with embedded maps of fully warmed up engine-out performance and emissions, and appropriate temperature-dependent correction factors to account for not fully warmed up conditions during transients. Similarly, engine-out emissions are converted to catalyst-out emissions using conversion efficiencies based on the catalyst brick temperature. A crucial element of the methodology is hence the ability to predict heat flows and component temperatures in the engine and the exhaust system during transients, consistent with the data available during concept definition and early design phases.

A regenerative braking model for a parallel Hybrid Electric Vehicle (HEV) is developed in this work. This model computes the line and pad pressures for the front and rear brakes, the amount of generator use depending on the state of deceleration (i.e. the brake pedal position), and includes a wheel lock-up avoidance algorithm. The regenerative braking model has been developed in the symbolic programming environment of MATLAB/SIMULINK/STATEFLOW for downloadability to an actual HEV's control system. The regenerative braking model has been incorporated in NREL's HEV system simulation called ADVISOR. Code modules that have been changed to implement the new regenerative model are described. Resulting outputs are compared to the baseline regenerative braking model in the parent code. The behavior of the HEV system (battery state of charge, overall fuel economy, and emissions characteristics) with the baseline and the proposed regenerative braking strategy are first compared.

Hybrid electric vehicle (HEV) is regarded as an important technology in solving the energy and environment crisis. In this paper, the HEV technology applied in passenger cars by major automotive OEMs such as Toyota, Honda, GM, Ford, Volkswagen, BMW are investigated. The configuration diagrams for each OEM are presented. Based on the architecture analysis, a classification is done according to similar structures and performances. Furthermore, a cost estimation methodology for HEV is presented based on the preliminary tear-down research done by Environment Protection Agency (EPA). Meanwhile, the logarithmic relationship between fuel consumption (FC) reduction and degree of hybridization (DOH) is discovered by investigating 30 different hybrid cars. Combining the cost estimation and relation between FC&DOH, the hybridization cost for cars to meet the FC regulations can be calculated.