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High hydrocarbon (HC) emission during a cold start still remains one of the major emission control challenges for spark ignition (SI) engines in spite of about three decades of research in this area. This paper proposes a cold start HC emission control strategy based on a reduced order modeling technique. A novel singular perturbation approximation (SPA) technique, based on the balanced realization principle, is developed for a nonlinear experimentally validated cold start emission model. The SPA reduced model is then utilized in the design of a model-based sliding mode controller (SMC). The controller targets to reduce cumulative tailpipe HC emission using a combination of fuel injection, spark timing, and air throttle / idle speed controls. The results from the designed multi-input multi-output (MIMO) reduced order SMC are compared with those from a full order SMC. The results show the reduced SMC outperforms the full order SMC by reducing both engine-out and tailpipe HC emission.

Vehicle operation during cold-start powertrain conditions can have a significant impact on drivability, fuel economy and tailpipe emissions in modern passenger vehicles. As efforts continue to maximize fuel economy in passenger vehicles, considerable engineering resources are being spent in order to reduce the consumption penalties incurred shortly after engine start and during powertrain warmup while maintaining suitably low levels of tailpipe emissions. Engine downsizing, advanced transmissions and hybrid-electric architecture can each have an appreciable effect on cold-start strategy and its impact on fuel economy. This work seeks to explore the cold-start strategy of several passenger vehicles with different powertrain architectures and to understand the resulting fuel economy impact relative to warm powertrain operation. To this end, four vehicles were chosen with different powertrain architectures.

Environmental awareness and fuel economy legislation has resulted in greater emphasis on developing more fuel efficient vehicles. As such, achieving fuel economy improvements has become a top priority in the automotive field. Companies are constantly investigating and developing new advanced technologies, such as hybrid electric vehicles, plug-in hybrid electric vehicles, improved turbo-charged gasoline direct injection engines, new efficient powershift transmissions, and lighter weight vehicles. In addition, significant research and development is being performed on energy management control systems that can improve fuel economy of vehicles. Another area of research for improving fuel economy and environmental awareness is based on improving the customer's driving behavior and style without significantly impacting the driver's expectations and requirements.

In this paper, the conversion of a production SUV to a hybrid electric vehicle with a drive system utilizing a planetary power-split transmission is presented. The uniqueness of this design comes from its ability to couple the advantages of a parallel hybrid with the advantages of a series hybrid. Depending on operating conditions and recent operating history, the drive system transitions to one of several driving modes. The drive system consists of a planetary gear set coupled to an alternator, motor, and internal combustion engine. It performs the power-split operation without the need for belt drives or clutching devices. The effects on driveability, manufacturing, fuel economy, emissions, and performance are presented along with the design, selection, and implementation of all of the vehicle conversion components.

Battery management system (BMS) plays a key role in the power management of hybrid electric vehicles (HEV). It measures the state of charge (SOC), state of health (SOH) of the battery, protects the battery package and extends cells' life cycles. For HEV applications, lithium-ion battery is usually selected as electric power source due to its high specific energy, high energy density, and long life cycle. However, the non-linear characteristic of a Li-ion battery, complicated electro-chemical model, and environmental factors, raises the difficulties in the real-time estimation of the SOC for a Li-ion battery. To address this challenge, a BMS for HEVs is modeled with MATLAB/Simulink. In addition, a regenerative braking control strategy is proposed to determine the magnitude of the regenerative torque based on the battery SOC.

Aluminum based brake rotors have been a priority research topic in the DOE 1999 Aluminum Industry Roadmap for the Automobile Market. After fourteen years, no satisfactory technology has been developed to solve the problem of aluminum's low working temperatures except the steel clad aluminum (SCA) brake technology. This technology research started at Michigan Technological University (MTU) in 2001 and has matured recently for commercial productions. The SCA brake rotor has a solid body and replaces the traditional convective cooling of a vented rotor with conductive cooling to a connected aluminum wheel. Much lower temperatures result with the aluminum wheel acting as a great heat sink/radiator. The steel cladding further increases the capability of the SCA rotor to withstand higher surface temperatures. During the road tests of SCA rotors on three cars, significant gas mileage improvement was found; primarily attributed to the unique capability of the SCA rotor on pad drag reduction.

A fast, semi-automated method for visualizing the time-varying effects of radiative heat transfer, including obscuration and multiple reflections, is presented. Starting with a finite element surface description, an analyst assigns “groups” to a model by indicating which elements have the same material and surface properties. The elements within each group are combined into isothermal nodes. View factors are then calculated using a variant of the hemi-cube method. Transient nodal temperatures are calculated using an implicit solution to the finite difference equations derived from the thermal properties of each node and the radiation exchange between nodes.

The formulation of mathematical model for the computational simulation of transient temperature response and phase change of refrigerant in a vapor condenser of an automotive air conditioning unit is described. A demonstrative computational simulation of a sample air cooled vapor condenser charged with Freon 12 is presented. The computational analysis predicts an initial surge and followed by an oscillation of the condensate outflow rate from the condenser when the air-conditioning unit is started, and the tube length required for complete condensation of inflow vapor is a maximum value at start up. The rise of the temperatures of the condenser tubes and cooling air flow during the start-up and load change operations rate found to be gradual but the scale of these temperature changes are considered small.

The effect of truck dieselization for three levels of diesel penetration into each of the eight classes of trucks is modeled. Diesel and total truck sales, population, mileage and yearly fuel usage data are aggregated by four truck classes representing light, medium, light-heavy and heavy-heavy classes. Four fuel economy scenario's for different technological improvements were studied. Improvement of fuel economy for light and heavy-heavy duty vehicle classes provides significant total fuel savings. Truck dieselization of light and light-heavy duty vehicle classes provides the largest improvement of fuel usage due to the fact that they have large numbers of vehicles and presently have few diesels. Total car and truck fuel usage in the 1980's shows roughly a constant demand with cars decreasing due to improved new fleet fuel economy and trucks increasing due to a larger population with better fuel economy due to dieselization and improved technology.

This paper studies model predictive control algorithm for Hybrid Electric Vehicle (HEV) energy management to improve HEV fuel economy. In this paper, Model Predictive Control (MPC), a predictive control method, is applied to improve the fuel economy of power-split HEV. A dedicated model predictive control method is developed to predict vehicle speed, battery state of charge (SOC), and engine fuel consumption. The power output from the engine, motor, and the mechanical brake will be adjusted to match driver's power request at the end of the prediction window while minimizing fuel consumption. The controller model is built on Matlab® MPC toolbox® and the simulations are based on MY04 Prius vehicle model using Autonomie®, a powertrain and fuel economy analysis software, developed by Argonne National Laboratory. The study compares the performance of MPC and conventional rule-base control methods.

Vehicles with power exporting capability are microgrids since they possess electrical power generation, onboard loads, energy storage, and the ability to interconnect. The unique load and silent watch requirements of some military vehicles make them particularly well-suited to augment stationary power grids to increase power resiliency and capability. Connecting multiple vehicles in a peer-to-peer arrangement or to a stationary grid requires scalable power management strategies to accommodate the possibly large numbers of assets. This paper describes a military ground vehicle power management scheme for vehicle-to-grid applications. The particular focus is overall fuel consumption reduction of the mixed asset inventory of military vehicles with diesel generators typically used in small unit outposts.

Two modern light-duty passenger vehicles were selected for chassis dynamometer testing to evaluate differences in performance end efficiency resulting from CNG and gasoline combustion in a vehicle-based context. The vehicles were chosen to be as similar as possible apart from fuel type, sharing similar test weights and identical driveline configurations. Both vehicles were tested over several chassis dynamometer driving cycles, where it was found that the CNG vehicle exhibited 3-9% lower fuel economy than the gasoline-fueled subject. Performance tests were also conducted, where the CNG vehicle's lower tractive effort capability and longer acceleration times were consistent with the lower rated torque and power of its engine as compared to the gasoline model. The vehicles were also tested using quasi-steady-state chassis dynamometer techniques, wherein a series of engine operating points were studied.

Engine friction serves as an important domain for study and research in the field of internal combustion engines. Research shows that friction between the piston and cylinder accounts for almost 20% of the losses in an engine and therefore any effort to minimize friction losses will have an immediate impact on engine efficiency and thus vehicle fuel economy. The two most common methods to experimentally measure engine friction are the floating liner method and the instantaneous indicated mean effective pressure (IMEP) method. This paper provides a detailed review of the IMEP method, presents major findings, and discusses sources of error. Although the instantaneous IMEP method is relatively new compared to the floating liner method, it has been used by many scientists and engineers for calculating piston ring assembly friction with consistent results.

Up to 80 percent of the total hydrocarbons emitted during the EPA Federal emissions test are produced in the first five minutes of this procedure. It has been theorized that this is in part due to wall wetting of the intake port and cylinder. This study measures the behavior of the fuel film thickness in the intake port during cold starting, steady state and transient operation. Three injector spray patterns with varying droplet sizes were utilized for the tests. The fuel film thickness in the intake port of a Ford 1.9L engine was measured using optical sensors. It was found that the spray pattern and droplet size affected the port wall wetting characteristics.