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Energy management is one of the key challenges for the development of Hybrid Electric Vehicle (HEV) due to its complex powertrain structure. Hardware-In-the-Loop (HIL) simulation provides an open software architecture which enables rapid prototyping HEV energy management system. This paper presents the investigation of the energy management system for a single shaft parallel hybrid electric vehicle using dSPACE eDrive HIL system. The parallel hybrid electric vehicle, energy management system, and low-level Electronic Control Unit (ECU) were modeled using dSPACE Automotive Simulation Models and dSPACE blocksets. Vehicle energy management is achieved by a vehicle-level controller called hybrid ECU, which controls vehicle operation mode and torque distribution among Internal Combustion Engine (ICE) and electric motor. The individual powertrain components such as ICE, electric motor, and transmission are controlled by low-level ECUs.

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.

This paper discusses the evaluation and application of a portable parked-vehicle tailpipe emissions measurement apparatus (EMA). The EMA consists of an exhaust dilution system and a portable instrument package. The EMA instantaneously dilutes and cools a sample of exhaust with compressed nitrogen or air at a known dilution ratio, thereby presenting it to instruments as it is presented to personnel in the surrounding environment. The operating principles and governing equations of the EMA are presented. A computational method is presented to determine the engine operating and performance parameters from the exhaust CO2 concentrations along with an assumed engine overall volumetric efficiency and brake specific fuel consumption. The parameters determined are fuel/air ratio, mass flow rates of fuel, air and exhaust emissions, and engine brake torque and horsepower.

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.

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.