Search Results

Alternative and renewable fuels show tremendous promise for addressing concerns of energy security, energy supply, and CO₂ emissions. However, the new fuels have the potential to produce non-regulated exhaust components that may be as detrimental or worse, than currently regulated emissions components. For the 2009 SAE Clean Snowmobile Challenge (CSC), a commercially available Fourier Transform Infrared (FTIR) spectrometer was used to sample raw exhaust from eight student teams' snowmobiles for comparative analysis with a conventional emissions bench. The levels of CO₂, CO, NO , O₂, and THC were compared for the five operating modes, which included both gasoline- and diesel-powered snowmobiles. The fuel was either an ethanol blend for spark-ignition engines or a biodiesel for compression-ignition engines. Final emissions result scores varied by less than 2% between the conventional emissions bench and the FTIR.

An operational scheme with fuel-lean and exhaust gas dilution in spark-ignited engines increases thermal efficiency and decreases NOx emission, while these operations inherently induce combustion instability and thus large cycle-to-cycle variation in engine. In order to stabilize combustion variations, the development of an advanced ignition system is becoming critical. To quantify the impact of spark-ignition discharge, ignitability tests were conducted in an optically accessible combustion vessel to characterize the flame kernel development of lean methane-air mixture with CO₂ simulating exhaust diluent. A shrouded fan was used to generate turbulence in the vicinity of J-gap spark plug and a Variable Output Ignition System (VOIS) capable of producing a varied set of spark discharge patterns was developed and used as an ignition source. The main feature of the VOIS is to vary the secondary current during glow discharge including naturally decaying and truncated with multiple strikes.

This paper studies the bi-directional power flow control between Plug-in Electric Vehicles (PEVs) and an electrical grid. A grid-tied charging system that enables both Grid-to-Vehicle (G2V) and Vehicle-to-Grid (V2G) charging/discharging is modeled using SimPowerSystems in Matlab/Simulink environment. A bi-directional AC-DC converter and a bi-directional DC-DC buck-boost converter are integrated to charge and discharge PEV batteries. For AC-DC converter control, Predictive Current Control (PCC) strategy is employed to enable grid current to reach a reference current after one modulation period. In addition, Phase Lock Loop (PLL) and a band-stop filter are designed to lock the grid voltage phase and reduce harmonics. Bi-directional power flow is realized by controlling the mode of the DC-DC converter. Simulation tests are conducted to evaluate the performance of this bi-directional charging system.

The vehicle driving cycles affect the performance of a hybrid vehicle control strategy, as a result, the overall performance of the vehicle, such as fuel consumption and emission. By identifying the driving cycles of a vehicle, the control system is able to dynamically change the control strategy (or parameters) to the best one to adapt to the changes of vehicle driving patterns. This paper studies the supervised driving cycle recognition using pattern recognition approach. With pattern recognition method, a driving cycle is represented by feature vectors that are formed by a set of parameters to which the driving cycle is sensitive. The on-line driving pattern recognition is achieved by calculating the feature vectors and classifying these feature vectors to one of the driving patterns in the reference database. To establish reference driving cycle database, the representative feature vectors for four federal driving cycles are generated using feature extraction method.

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.

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.

Particulate emission from diesel engines is one of the most important pollutants in urban areas. As a result, particulate emission control from urban bus diesel engines using particle filter technology is being evaluated at several locations in the US. A project entitled “Clean Diesel Demonstration Program” has been initiated by NY City Transit under the supervision of NY State DEC and with active participation from several industrial partners. Under this program, several NY City transit buses with DDC Series 50 engines have been equipped with continuously regenerating diesel particulate filter system and are operating with ultra low sulfur diesel (< 30 ppm S) in transit service in Manhattan since February 2000. These buses are being evaluated over a 8-9 month period for operations, maintainability and durability of the particulate filter.

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 successful implementation of a clean, quiet, four-stroke engine into an existing snowmobile chassis has been achieved. The snowmobile is easy to start, easy to drive and environmentally friendly. The following paper describes the conversion process in detail with actual engine test data. The hydrocarbon emissions of the new, four-stroke snowmobile are 98% lower than current, production, two-stroke models. The noise production of the four-stroke snowmobile was 68 dBA during an independent wide open throttle acceleration test. If the four-stroke snowmobile were to replace all current, two-stroke snowmobiles in Yellowstone National Park (YNP), the vehicles would only produce 16% of the combined automobile and snowmobile hydrocarbon emissions compared to the current 93% produced by two-stroke snowmobiles.

In urban areas, particulate emission from diesel engines is one of the pollutants of most concern. As a result, particulate emission control from urban bus diesel engines using particle filter technology is being evaluated at several locations in the US. A project entitled, “Clean Diesel Vehicle Air Quality Project” has been initiated by NY City Transit under the supervision of NYSDEC and with active participation from several industry partners. Under this program, 25 NY City transit buses with DDC Series 50 engines have been equipped with continuously regenerating diesel particulate filter systems and have been operating with ultra low sulfur diesel (< 30 ppm S) in transit service in Manhattan since February 2000. These buses were evaluated over a 9 month period for operations, maintainability and durability of the particulate filter.

Low Temperature Combustion (LTC) engines are promising to improve powertrain fuel economy and reduce NOx and soot emissions by improving the in-cylinder combustion process. However, the narrow operating range of LTC engines limits the use of these engines in conventional powertrains. Extended range electric vehicles (EREVs), by decoupling the engine from the drivetrain, allows the engine to operate in a limited operating range; thus, EREVs offer an ideal platform for realizing the advantages of LTC engines. In this study, the global optimum fuel economy improvement of an experimentally developed 2-liter multi-mode LTC engine in a series EREV is investigated. The engine operation modes include Homogeneous-Charge Compression Ignition (HCCI), Reactivity Controlled Compression Ignition (RCCI), and conventional Spark Ignition (SI).

This paper presents results on how the Equivalent Consumption Minimization Strategy (ECMS) penalty factor effects Lithium ion battery aging. The vehicle studied is the Honda Civic Hybrid. The battery used is A123 Systems’. Vehicle simulation using multiple combinations of highway and city drive cycles. For each combination of drive cycles, six ECMS penalty factor values are used. Battery aging is evaluated using a semi-empirical model combined with accumulated Ah-throughput method which uses, as an input, the battery state of charge trajectory from the vehicle simulations. The tradeoff between fuel cost and battery aging cost is explicitly displayed. In addition, the results provide insight into how driving behavior affects battery aging. The paper concludes with a discussion of the optimal balance between fuel cost and battery aging.

The automotive industry continues to develop technologies for reducing vehicle fuel consumption. Specifically, vehicle lightweighting is expected to be a key enabler for achieving fleet CO2 reduction targets for 2025 and beyond. Hybrid glass laminates that incorporate fusion draw and ion exchange innovations are thinner and thereby, offer more than 30% weight reduction compared to conventional automotive laminates. These lightweight hybrid laminates provide additional benefits, including improved toughness and superior optics. However, glazing weight reduction leads to an increase in transmission of sound through the laminates for certain frequencies. This paper documents a study that uses a systematic test-based approach to understand the sensitivity of interior vehicle noise behavior to changes in acoustic attenuation driven by installation of lightweight glass.

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.

The motorcycle emissions regulations for both two-stroke and four-stroke engines, which are receiving worldwide attention, will go into effect in the very near future. To meet these regulations, the motorcycles will require a catalyst in conjunction with the muffler due to space limitations. The combination of high engine speeds, high vibrational acceleration, high HC and CO emissions, high oxidation exotherms, and stringent durability requirements, points to cordierite ceramic substrate as an ideal catalyst support. However, as an integral unit within the muffler, its packaging design must be capable of withstanding isothermal operating conditions which may exceed the upper intumescent temperature limit of the ceramic mat. This paper describes a durable packaging design for the ceramic catalyst which employs a hybrid ceramic mat, special end rings and gaskets, and high strength stainless steel can.

A mathematical model is presented for analysis and optimization of the adsorbents in the multifiltration beds contained in the International Space Station (ISS) water processor. The model consists of a physical properties database, an equilibrium description for single and multicomponent adsorption, and a kinetic description for adsorption beds in the water processor. The model is verified on a surrogate mixture designed to mimic the adsorption potential of the ISS shower/handwash waste stream.

The destruction of organic contaminants in waste water for closed systems, such as that of the International Space Station, is crucial due to the need for recycling the waste water. A cocurrent upflow bubble column using oxygen as the gas phase oxidant and packed with catalyst particles consisting of a noble metal on an alumina substrate is being developed for this process. This paper addresses the development of a plug-flow model that will predict the performance of this three phase reactor system in destroying a multicomponent mixture of organic contaminants in water. Mass balances on a series of contaminants and oxygen in both the liquid and gas phases are used to develop this model. These mass balances incorporate the gas-to-liquid and liquid-to-particle mass transfer coefficients, the catalyst effectiveness factor, and intrinsic reaction rate.

A mathematical model is presented for analysis and optimization of the ion exchange beds in the International Space Station (ISS) Water Processor. The model consists of a physical properties database, an equilibrium description for binary and multicomponent ion exchange, and a kinetic description for ion exchange beds in the Water Processor. The ion exchange model will be verified for an Ersatz water designed to mimic the ISS shower/handwash waste stream.

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.