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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.

The objective of this research was to evaluate the effects that higher fluid injection pressures and nozzle geometry have on compound fuel injector nozzle performance. Higher pressures are shown to significantly reduce droplet size, increase the discharge coefficient and reduce the overall size of a nozzle spray. It is also shown that the geometry has a significant effect on nozzle performance, and it can be manipulated to give a desired spray shape.

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.

The National Science Foundation recently sponsored a Workshop on Environmentally Benign Manufacturing (EBM) for the Transportation Industries. The objective of the workshop was to determine future directions of research in the EBM area and to construct a roadmap for development of future research programs. While research in the fields of Design for the Environment (DfE) and Life Cycle Analysis (LCA) have focused on the product and product life cycles, an additional focus is needed to find and develop processes with less environmental impact within the manufacturing environment. This workshop explored EBM issues with respect to the enterprise, the products, the processes and the materials.

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.

Studies have been conducted at Michigan Technological University (MTU) for over twenty years on methods for characterizing and controlling particulate emissions from heavy-duty diesel engines and the resulting effects on regulated and unregulated emissions. During that time, control technologies have developed in response to more stringent EPA standards for diesel emissions. This paper is a review of: 1) modern emission control technologies, 2) emissions sampling and chemical, physical and biological characterization methods and 3) summary results from recent studies conducted at MTU on heavy-duty diesel engines with a trap and an oxidation catalytic converter (OCC) operated on three different fuels. Control technology developments discussed are particulate traps, catalysts, advances in engine design, the application of exhaust gas recirculation (EGR), and modifications of fuel formulations.

The objective in this research is to investigate the effects of variable blank holder force (VBHF) on the material formability, due to its effect on the strain path. It is found in a recent study [9] that VBHF does not significantly affect the overall trend of the strain path. This strain path in deep drawing process is linear for the materials in the flange and under punch face, and is roughly bi-linear for the material around the punch nose. The second segment of the strain path in the punch nose region is plane-strain. VBHF, however, affects the strain ratio ρ1 = ε2/ε1 of the first segment of the bi-linear strain path. These effects, especially ρ1, on limit strain were studied using M-K method. A strain path dependent modified forming limit diagram (MFLD) was calculated based on the actual strain path. It is found that the MFLD is strongly dependent on ρ1.

The goal of this research was to determine an empirical method of relating the droplet sizes and the spray patterns to the parameters and the geometries of the compound nozzles. Two different types of compound nozzles were studied, the compound silicon micro machined nozzle and the compound metal disk nozzle. Several different orifice geometries of each nozzle type were examined. The injector components upstream of the compound nozzle of two different types of injectors were also studied. A nondimensional characterization of the droplet sizes and the mass flow rates was proposed. The results of this study show that there exists optimum geometric features that will produce sprays with the minimum steady state and dynamic Sauter mean diameter. The spray of a compound nozzle can be characterized by the atomization efficiency and the discharge coefficient. Nozzle testing results show that many flow characteristics are developed in the compound nozzle.

The current trend in the automotive industry is to minimize/eliminate cutting fluid use in most machining operations. Research is required prior to achieving dry or semi-dry machining. Issues such as heat generation and transfer, thermal deformation and fluid lubricity related effects on tool life and surface roughness determine the feasibility of dry machining. This paper discusses recent advances in achieving dry/semi-dry machining. As the first step, research has been conducted to investigate the actual role of fluids (if any) in various machining operations. A predictive heat generation model for orthogonal cutting of visco-plastic material was created. A control volume approach allowed development of a thermal model for convective heat transfer during machining. The heat transfer performance of an air jet in dry machining was explored. The influence of machining process variables and cutting fluid presence on chip morphology was investigated through designed experiments.

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.

A major task of road and airfield maintenance for transportation departments in the Northern United States and in cold regions globally is snow removal. In addition, there is a service industry built on snowplow equipped light trucks to remove snow from vehicle serviceways and parking lots. Thus, a source of stresses on a truck frame are the forces applied by the plow. Unfortunately, very little research has been performed to provide design models that will predict these forces. In this paper, both theoretical and experimental work on developing expressions for snowplow forces will be discussed.