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Lithium-ion (Li-ion) batteries are becoming widely used high-energy sources and a replacement of the Nickel Metal Hydride batteries in electric vehicles (EV), hybrid electric vehicles (HEV) and plug-in hybrid electric vehicles (PHEV). Because of their light weight and high energy density, Li-ion cells can significantly reduce the weight and volume of the battery packs for EVs, HEVs and PHEVs. Some materials in the Li-ion cells have low thermal stabilities and they may become thermally unstable when their working temperature becomes higher than the upper limit of allowed operating temperature range. Thus, the cell working temperature has a significant impact on the life of Li-ion batteries. A proper control of the cell working temperature is crucial to the safety of the battery system and improving the battery life. This paper outlines an approach for the thermal analysis of Li-ion battery cells and modules.

This paper proposes a framework to perform design optimization of a series PHEV and investigates the impact of using real-world driving inputs on final design. Real-World driving is characterized from a database of naturalistic driving generated in Field Operational Tests. The procedure utilizes Markov chains to generate synthetic drive cycles representative of real-world driving. Subsequently, PHEV optimization is performed in two steps. First the optimal battery and motor sizes to most efficiently achieve a desired All Electric Range (AER) are determined. A synthetic cycle representative of driving over a given range is used for function evaluations. Then, the optimal engine size is obtained by considering fuel economy in the charge sustaining (CS) mode. The higher power/energy demands of real-world cycles lead to PHEV designs with substantially larger batteries and engines than those developed using repetitions of the federal urban cycle (UDDS).

Because of U.S. EPA regulatory actions and the National Academies National Research Council suggestions for improvements in the U.S. EPA emissions inventory methods, the U.S. EPA' Office of Transportation and Air Quality (OTAQ) has made a concerted effort to develop instrumentation that can measure criteria pollutant emissions during the operation of on-road and off-road vehicles. These instruments are now being used in applications ranging from snowmobiles to on-road passenger cars to trans-Pacific container ships. For the betterment of emissions inventory estimation these on-vehicle instruments have recently been employed to measure time resolved (1 hz) in-use gaseous emissions (CO₂, CO, THC, NO ) and particulate matter mass (with teflon membrane filter) emissions from 29 non-road construction vehicles (model years ranging from 1993 to 2007) over a three year period in various counties in Iowa, Missouri, and Kansas.

Electric vehicles are receiving considerable attention because they offer a more efficient and sustainable transportation alternative compared to conventional fossil-fuel powered vehicles. Since the battery pack represents the primary energy storage component in an electric vehicle powertrain, it requires accurate monitoring and control. In order to effectively estimate the battery pack critical parameters such as the battery state of charge (SOC), state of health (SOH), and remaining capacity, a high-fidelity battery model is needed as part of a robust SOC estimation strategy. As the battery degrades, model parameters significantly change, and this model needs to account for all operating conditions throughout the battery's lifespan. For effective battery management system design, it is critical that the physical model adapts to parameter changes due to aging.

The benchmarking study described in this paper uses data from chassis dynamometer testing to determine the efficiency and operation of vehicle driveline components. A robust test procedure was created that can be followed with no a priori knowledge of component performance, nor additional instrumentation installed in the vehicle. To develop the procedure, a 2013 Chevrolet Malibu was tested on a chassis dynamometer. Dynamometer data, emissions data, and data from the vehicle controller area network (CAN) bus were used to construct efficiency maps for the engine and transmission. These maps were compared to maps of the same components produced from standalone component benchmarking, resulting in a good match between results from in-vehicle and standalone testing. The benchmarking methodology was extended to a 2013 Mercedes E350 diesel vehicle. Dynamometer, emissions, and CAN data were used to construct efficiency maps and operation strategies for the engine and transmission.

Chassis dynamometer tests were conducted on three Class III on-highway motorcycles produced for the North American market and equipped with advanced emission control technologies in order to inform emissions inventories and compare the impacts of existing Tier 2 (E0) fuel with more market representative Tier 3 and LEV III certification fuels with 10% ethanol. For this study, the motorcycles were tested over the US Federal Test Procedure (FTP) and the World Motorcycle Test Cycle (WMTC) certification test cycles as well as a sample of real-world motorcycle driving informally referred to as the Real World Driving Cycle (RWDC). The primary interest was to understand the emissions changes of the selected motorcycles with the use of certification fuels containing 10% ethanol compared to 0% ethanol over the three test cycles.

As part of the U.S. Environmental Protection Agency’s (EPA’s) continuing assessment of advanced light-duty automotive technologies in support of regulatory and compliance programs, a 2018 Toyota Camry front wheel drive eight-speed automatic transmission was benchmarked. The benchmarking data were used as inputs to EPA’s Advanced Light-duty Powertrain and Hybrid Analysis (ALPHA) vehicle simulation model to estimate GHG emissions from light-duty vehicles. ALPHA requires both detailed engine fuel consumption maps and transmission torque loss maps. EPA’s National Vehicle and Fuels Emissions Laboratory has developed a streamlined, cost-effective in-house method of transmission testing, capable of gathering a dataset sufficient to characterize transmissions within ALPHA. This testing methodology targets the range of transmission operation observed during vehicle testing over EPA’s city and highway drive cycles.

The Advanced Light-Duty Powertrain and Hybrid Analysis (ALPHA) tool was created by EPA to estimate greenhouse gas (GHG) emissions from light-duty (LD) vehicles [1]. ALPHA is a physics-based, forward-looking, full vehicle computer simulation capable of analyzing various vehicle types combined with different powertrain technologies. The software tool is a MATLAB/Simulink based desktop application. In order to model the behavior of current and future vehicles, an algorithm was developed to dynamically generate transmission shift logic from a set of user-defined parameters, a cost function (e.g., engine fuel consumption) and vehicle performance during simulation. This paper presents ALPHA's shift logic algorithm and compares its predicted shift points to actual shift points from a mid-size light-duty vehicle and to the shift points predicted using a static table-based shift logic as calibrated to the same vehicle during benchmark testing.

This paper addresses scheduling of quantized power levels (including part load operation and startup/shutdown periods) for a propane powered solid oxide fuel cell (SOFC) hybridized with a lithium-ion battery for a tracked mobile robot. The military requires silent operation and long duration missions, which cannot be met by batteries alone due to low energy density or with combustion engines due to noise. To meet this need we consider an SOFC operated at a few discrete power levels where maximum system efficiency can be achieved. The fuel efficiency decreases during transients and resulting thermal gradients lead to stress and degradation of the stack; therefore switching power levels should be minimized. Excess generated energy is used to charge the battery, but when it’s fully charged the SOFC should be turned off to conserve fuel.

The U.S. Environmental Protection Agency’s (EPA’s) Advanced Light-Duty Powertrain and Hybrid Analysis (ALPHA) tool was created to estimate greenhouse gas (GHG) emissions from light-duty vehicles. ALPHA is a physics-based, forward-looking, full vehicle computer simulation capable of analyzing various vehicle types with different powertrain technologies, showing realistic vehicle behavior, and auditing of all energy flows in the model. In preparation for the midterm evaluation (MTE) of the 2017-2025 light-duty GHG emissions rule, ALPHA has been refined and revalidated using newly acquired data from model year 2013-2016 engines and vehicles. The robustness of EPA’s vehicle and engine testing for the MTE coupled with further validation of the ALPHA model has highlighted some areas where additional data can be used to add fidelity to the engine model within ALPHA.

This study uses full drive cycle simulation to compare the fuel consumption of a vehicle with a turbocharged (TC) engine to the same vehicle with an alternative boosting technology, namely, a hybrid supercharger, in which a planetary gear mechanism governs the power split to the supercharger between the crankshaft and a 48 V 5 kW electric motor. Conventional mechanically driven superchargers or electric superchargers have been proposed to improve the dynamic response of boosted engines, but their projected fuel efficiency benefit depends heavily on the engine transient response and driver/cycle aggressiveness. The fuel consumption benefits depend on the closed-loop engine responsiveness, the control tuning, and the torque reserve needed for each technology. To perform drive cycle analyses, a control strategy is designed that minimizes the boost reserve and employs high rates of combustion dilution via exhaust gas recirculation (EGR).

A GT-SUITE vehicle-aftertreatment model has been developed to examine the cold-start emissions reduction capabilities of a Vacuum Insulated Catalytic Converter (VICC). This converter features a thermal management system to maintain the catalyst monolith above its light-off temperature between trips so that most of a vehicle’s cold-start exhaust emissions are avoided. The VICC thermal management system uses vacuum insulation around the monoliths. To further boost its heat retention capacity, a metal phase-change material (PCM) is packaged between the monoliths and vacuum insulation. To prevent overheating of the converter during periods of long, heavy engine use, a few grams of metal hydride charged with hydrogen are attached to the hot side of the vacuum insulation. The GT-SUITE model successfully incorporated the transient heat transfer effects of the PCM using the effective heat capacity method.

Reducing the weight of the M1A2 tank by lightweighting hull, suspension, and track results in 5.1%, 1.3%, and 0.6% tank mass reductions, respectively. The impact of retrofitting with lightweight components is evaluated through primary energy demand (PED), cost, and fuel consumption (FC). Life cycle stages included are preproduction (design, prototype, and testing), material production, part fabrication, and operation. Metrics for lightweight components are expressed as ratios comparing lightweighted and unmodified tanks. Army-defined drive cycles were employed and an FC vs. mass elasticity of 0.55 was used. Depending on the distance traveled, cost to retrofit and operate a tank with a lightweighted hull is 3.5 to 19 times the cost for just operating an unmodified tank over the same distance. PED values for the lightweight hull are 1.1 to 2 times the unmodified tank. Cost and PED ratios decrease with increasing distance.

This investigation was aimed at measuring the relative performance of two spray-guided, single-cylinder, spark-ignited direct-injected (SIDI) engine combustion system designs. The first utilizes an outwardly-opening poppet, piezo-actuated injector, and the second a conventional, solenoid operated, inwardly-opening multi-hole injector. The single-cylinder engine tests were limited to steady state, warmed-up conditions. The comparison showed that these two spray-guided combustion systems with two very different sprays had surprisingly close results and only differed in some details. Combustion stability and smoke emissions of the systems are comparable to each other over most of the load range. Over a simulated Federal Test Procedure (FTP) cycle, the multi-hole system had 15% lower hydrocarbon and 18% lower carbon monoxide emissions.

The temperature distribution is studied theoretically in a battery module stacked with 12 high-power Li-ion pouch cells. The module is cooled indirectly with ambient air through aluminum heat-sink plates or cooling plates sandwiched between each pair of cells in the module. Each of the cooling plates has an extended cooling fin exposed in the cooling air channel. The cell temperatures can be controlled by changing the air temperature and/or the heat transfer coefficient on the cooling fin surfaces by regulating the air flow rate. It is found that due to the high thermal conductivity and thermal diffusivity of the cooling plates, heat transfer of the cooling plate governs the cell temperature distribution by spreading the cell heat over the entire cell surface. Influence of thermal from the cooling fins is also simulated.

Ideal operation temperatures for Li-ion batteries fall in a narrow range from 20°C to 40°C. If the cell operation temperatures are too high, active materials in the cells may become thermally unstable. If the temperatures are too low, the resistance to lithium-ion transport in the cells may become very high, limiting the electrochemical reactions. Good battery thermal management is crucial to both the battery performance and life. Characteristics of various battery thermal management systems are reviewed. Analyses show that the advantages of direct and indirect air cooling systems are their simplicity and capability of cooling the cells in a battery pack at ambient temperatures up to 40°C. However, the disadvantages are their poor control of the cell-to-cell differential temperatures in the pack and their capability to dissipate high cell generations.

Electrification and hybridization have great potential for improving fuel economy and reducing visual signature or soot emissions in military vehicles. Specific challenges related to military applications include severe duty cycles, large and uncertain energy flows through the system and high thermal loads. A novel supervisory control strategy is proposed to simultaneously mitigate severe engine transients and to reduce high electric current in the battery without oversizing the battery. The described objectives are accomplished by splitting the propulsion power demand through filtering in the frequency domain. The engine covers only low frequency power demand profile while the battery covers high frequency components. In the proposed strategy, the separation filter is systematically designed to identify different frequency components with the consideration of fuel consumption, aggressive engine transients, and battery electric loads.

Thermal behavior of a lithium-ion (Li-ion) battery module for hybrid electrical vehicle (HEV) applications is analyzed in this study. The module is stacked with 12 high-power pouch Li-ion battery cells. The cells are cooled indirectly with air through aluminum fins sandwiched between each two cells in the module, and each of the cooling fins has an extended cooling surface exposed in the cooling air flow channel. The cell temperatures are analyzed using a quasi-dimensional model under both the transient module load in a user-defined cycle for the battery system utilizations and an equivalent continuous load in the cycle. The cell thermal behavior is evaluated with the volume averaged cell temperature and the cell heat transfer is characterized with resistances for all thermal links in the heat transfer path from the cell to the cooling air. Simulations results are compared with measurements. Good agreement is observed between the simulated and measured cell temperatures.

The increasing numbers of hybrid electric and full electric vehicle models currently in the market or in the pipeline of automotive OEMs require creative testing mechanisms to drive down development costs and optimize the efficiency of these vehicles. In this paper, such a testing mechanism that has been successfully implemented at the US Environmental Protection Agency National Vehicle and Fuel Emissions Laboratory (EPA NVFEL) is described. In this testing scheme, the units-under-test consist of a battery pack and its associated battery management system (BMS). The remaining subsystems, components, and environment of the vehicle are virtual and modeled in high fidelity.

This paper summarizes the Heavy-Duty In-Use Testing (HDUIT) measurement allowance program for Particulate Matter Portable Emissions Measurement Systems (PM-PEMS). The measurement allowance program was designed to determine the incremental error between PM measurements using the laboratory constant volume sampler (CVS) filter method and in-use testing with a PEMS. Two independent PM-PEMS that included the Sensors Portable Particulate Measuring Device (PPMD) and the Horiba Transient Particulate Matter (TRPM) were used in this program. An additional instrument that included the AVL Micro Soot Sensor (MSS) was used in conjunction with the Sensors PPMD to be considered a PM-PEMS. A series of steady state and transient tests were performed in a 40 CFR Part 1065 compliant engine dynamometer test cell using a 2007 on-highway heavy-duty diesel engine to quantify the accuracy and precision of the PEMS in comparison with the CVS filter-based method.