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With the introduction of plug-in electric vehicles (PEVs), the conventional mindset of “fill-up time” will be challenged as customers top off their battery packs. For example, using a standard 120VAC outlet, it may take over 10hrs to achieve 40-50 miles of EV range-making range anxiety a daunting reality for EV owners. As customers adapt to this new mindset of charge time, it is critical that automotive OEMs supply the consumer with accurate charge time estimates. Charge time accuracy relies on a variety of parameters: battery pack size, power source, electric vehicle supply equipment (EVSE), on-board charging equipment, ancillary controller loads, battery temperature, and ambient temperature. Furthermore, as the charging events may take hours, the initial conditions may vary throughout a plug-in charge (PIC). The goal of this paper is to characterize charging system sensitivities and promote best practices for charge time estimations.

Fuel injection during negative valve overlap offers a promising method of controlling HCCI combustion, but sorting out the thermal and chemical effects of NVO fueling requires knowledge of temperatures throughout the cycle. Computing bulk temperatures throughout closed portions of the cycle is relatively straightforward using an equation of state, once a temperature at one crank angle is established. Unfortunately, computing charge temperatures at intake valve closing for NVO operation is complicated by a large, unknown fraction of residual gases at unknown temperature. To address the problem, we model blowdown and recompression during exhaust valve opening and closing events, allowing us to estimate in-cylinder charge temperatures based on exhaust-port measurements. This algorithm permits subsequent calculation of crank-angle-resolved bulk temperatures and residual gas fraction over a wide range of NVO operation.

Since transient vehicle HVAC computational fluids (CFD) simulations take too long to solve in a production environment, the goal of this project is to automatically create a lumped-parameter flow network from a steady-state CFD that solves nearly instantaneously. The data mining algorithm k-means is implemented to automatically discover flow features and form the network (a reduced order model). The lumped-parameter network is implemented in the commercial thermal solver MuSES to then run as a fully transient simulation. Using this network a “localized heat transfer coefficient” is shown to be an improvement over existing techniques. Also, it was found that the use of the clustering created a new flow visualization technique. Finally, fixing clusters near equipment newly demonstrates a capability to track localized temperatures near specific objects (such as equipment in vehicles).

This paper first summarizes a new theoretical description that quantifies the effects of real-fluid thermodynamics on liquid fuel injection processes as a function of pressure at typical engine operating conditions. It then focuses on the implications this has on modeling such flows with emphasis on application of the Large Eddy Simulation (LES) technique. The theory explains and quantifies the major differences that occur in the jet dynamics compared to that described by classical spray theory in a manner consistent with experimental observations. In particular, the classical view of spray atomization as an appropriate model at some engine operating conditions is questionable. Instead, non-ideal real-fluid behavior must be taken into account using a multicomponent formulation that applies to hydrocarbon mixtures at high-pressure supercritical conditions.

A detailed understanding of the various factors affecting the trends in gross-indicated thermal efficiency with changes in key operating parameters has been carried out, applied to a one-liter displacement single-cylinder boosted Low-Temperature Gasoline Combustion (LTGC) engine. This work systematically investigates how the supplied fuel energy splits into the following four energy pathways: gross-indicated thermal efficiency, combustion inefficiency, heat transfer and exhaust losses, and how this split changes with operating conditions. Additional analysis is performed to determine the influence of variations in the ratio of specific heat capacities (γ) and the effective expansion ratio, related to the combustion-phasing retard (CA50), on the energy split. Heat transfer and exhaust losses are computed using multiple standard cycle analysis techniques. The various methods are evaluated in order to validate the trends.

Battery temperature variations have a strong effect on both battery aging and battery performance. Significant temperature variations will lead to different battery behaviors. This influences the performance of the Hybrid Electric Vehicle (HEV) energy management strategies. This paper investigates how variations in battery temperature will affect Lithium-ion battery aging and fuel economy of a HEV. The investigated energy management strategy used in this paper is the Equivalent Consumption Minimization Strategy (ECMS) which is a well-known energy management strategy for HEVs. The studied vehicle is a Honda Civic Hybrid and the studied battery, a BLS LiFePO4 3.2Volts 100Ah Electric Vehicle battery cell. Vehicle simulations were done with a validated vehicle model using multiple combinations of highway and city drive cycles. The battery temperature variation is studied with regards to outside air temperature.

This paper presents a combined numerical and experimental investigation of the characteristics of spark discharge in a spark-ignition engine. The main objective of this work is to gain insights into the spark discharge process and early flame kernel development. Experiments were conducted in an inert medium within an optically accessible constant-volume combustion vessel. The cross-flow motion in the vessel was generated using a previously developed shrouded fan. Numerical modeling was based on an existing discharge model in the literature developed by Kim and Anderson. However, this model is applicable to a limited range of gas pressures and flow fields. Therefore, the original model was evaluated and improved to predict the behavior of spark discharge at pressurized conditions up to 45 bar and high-speed cross-flows up to 32 m/s. To accomplish this goal, a parametric study on the spark channel resistance was conducted.

The study of spray-wall interaction is of great importance to understand the dynamics that occur during fuel impingement onto the chamber wall or piston surfaces in internal combustion engines. It is found that the maximum spreading length of an impinged droplet can provide a quantitative estimation of heat transfer and energy transformation for spray-wall interaction. Furthermore, it influences the air-fuel mixing and hydrocarbon and particle emissions at combusting conditions. In this paper, an analytical model of a single diesel droplet impinging on the wall with different inclined angles (α) is developed in terms of βm (dimensionless maximum spreading length, the ratio of maximum spreading length to initial droplet diameter) to understand the detailed impinging dynamic process.

This paper considers optimal power management during the establishment of an expeditionary outpost using battery and vehicle assets for electrical generation. The first step in creating a new outpost is implementing the physical protection and barrier system. Afterwards, facilities that provide communications, fires, meals, and moral boosts are implemented that steadily increase the electrical load while dynamic events, such as patrols, can cause abrupt changes in the electrical load profile. Being able to create a fully functioning outpost within 72 hours is a typical objective where the electrical power generation starts with batteries, transitions to gasoline generators and is eventually replaced by diesel generators as the outpost matures. Vehicles with power export capability are an attractive supplement to this electrical power evolution since they are usually on site, would reduce the amount of material for outpost creation, and provide a modular approach to outpost build-up.

Computational fluid dynamics of gas-fueled large-bore spark ignition engines with pre-chamber ignition can speed up the design process of these engines provided that 1) the reliability of the results is not affected by poor meshing and 2) the time cost of the meshing process does not negatively compensate for the advantages of running a computer simulation. In this work a flame propagation model that runs with arbitrary hybrid meshes was developed and coupled with the KIVA4-MHI CFD solver, in order to address these aims. The solver follows the G-Equation level-set method for turbulent flame propagation by Tan and Reitz, and employs improved numerics to handle meshes featuring different cell types such as hexahedra, tetrahedra, square pyramids and triangular prisms. Detailed reaction kinetics from the SpeedCHEM solver are used to compute the non-equilibrium composition evolution downstream and upstream of the flame surface, where chemical equilibrium is instead assumed.

Developing an improved understanding of transient mixing and combustion processes inherent in diesel injection is an important element in the design of advanced engines. This paper provides a detailed analysis of these processes using an idealized benchmark configuration designed to facilitate precise comparisons between different models and numerical methods. The computational domain is similar to the Engine Combustion Network (www.sandia.gov/ECN) Spray-A injector with n-dodecane as the fuel. Quantified idealizations are made in the treatment of boundary conditions to eliminate ambiguities and unknowns associated with the actual injector(s) used in the experiment. These ambiguities hinder comparisons aimed at understanding the accuracy of different models and the coupled effects of potential numerical errors.

This paper investigates an optimal design of a diesel engine and after-treatment systems for a series hybrid electric forklift application. A holistic modeling approach is developed in GT-Suite® to establish a model-based hardware definition for a diesel engine and an after-treatment system to accurately predict engine performance and emissions. The used engine model is validated with the experimental data. The engine design parameters including compression ratio, boost level, air-fuel ratio (AFR), injection timing, and injection pressure are optimized at a single operating point for the series hybrid electric vehicle, together with the performance of the after-treatment components. The engine and after-treatment models are then coupled with a series hybrid electric powertrain to evaluate the performance of the forklift in the standard VDI 2198 drive cycle.

Minimizing heat-transfer (HT) losses is important for both improving engine efficiency and increasing exhaust energy for turbocharging and exhaust aftertreatment management, but engine combustion system design to minimize these losses is hindered by significant uncertainties in prediction. Empirical HT correlations such as the popular Woschni model have been developed and various attempts at improving predictions have been proposed since the 1960s, but due to variations in facilities and techniques among various studies, comparison and assessment of modelling approaches among multiple combustion modes is not straightforward. In this work, simultaneous cylinder-wall temperature and OH* chemiluminescence high-speed video are all recorded in a single heavy-duty optical engine operated under multiple combustion modes. OH* chemiluminescence images provide additional insights for identifying the causes of near-wall heat flux changes.

Autonomous vehicle operation is dependent upon accurate position estimation and thus a major concern of implementing the autonomous navigation is obtaining robust and accurate data from sensors. This is especially true, in case of Inertial Measurement Unit (IMU) sensor data. The IMU consists of a 3-axis gyro, 3-axis accelerometer, and 3-axis magnetometer. The IMU provides vehicle orientation in 3D space in terms of yaw, roll and pitch. Out of which, yaw is a major parameter to control the ground vehicle’s lateral position during navigation. The accelerometer is responsible for attitude (roll-pitch) estimates and magnetometer is responsible for yaw estimates. However, the magnetometer is prone to environmental magnetic disturbances which induce errors in the measurement.

Lithium-Ion batteries are being considered as a high-energy density replacement for Nickel Metal Hydride (NiMH) batteries in Hybrid Electric Vehicles (HEVs) and in the new Plug-In Hybrids (PHEVs). Although these cells can result in significant reduction in weight and volume, they have several safety related issues that still need to be addressed. We report here on the thermal response of Li-ion cells specifically assembled in our laboratory to test new materials, electrolytes and additives. Improvements in the thermal abuse tolerance of cells will be presented and discussed in terms of the need for overall battery system safety.

Mid 2006 a study group at General Motors developed the concept for the electric vehicle with extended range (EREV),. The electric propulsion system should receive the electrical energy from a rechargeable energy storage system (RESS) and/or an auxiliary power unit (APU) which could either be a hydrogen fuel cell or an internal combustion engine (ICE) driven generator. The study result was the Chevrolet VOLT concept car in the North American Auto Show in Detroit in 2007. The paper describes the requirements, concepts, development and the performance of the battery used as RESS for the ICE type VOLTEC propulsion system version of the Chevrolet Volt. The key requirement for the RESS is to provide energy to drive an electric vehicle with “no compromised performance” for 40 miles. Extended Range Mode allows for this experience to continue beyond 40 miles.

This paper1 explores some of the important considerations in devising a practical and consistent framework and methodology for working with experiments and experimental data in connection with modeling and prediction. The paper outlines a pragmatic and versatile “real-space” approach within which experimental and modeling uncertainties (correlated and uncorrelated, systematic and random, aleatory and epistemic) are treated to mitigate risk in modeling and prediction. The elements of data conditioning, model conditioning, model validation, hierarchical modeling, and extrapolative prediction under uncertainty are examined. An appreciation can be gained for the constraints and difficulties at play in devising a viable end-to-end methodology. The considerations and options are many, and a large variety of viewpoints and precedents exist in the literature, as surveyed here. Rationale is given for the various choices taken in assembling the novel real-space end-to-end framework.

Cast aluminum alloys are normally quenched after solution treatment or solidification process to improve aging responses. Rapid quenching can lead to high residual stress and severe distortion which significantly affects dimension stability, functionality and particularly performance of the product. To simulate residual stress and distortion induced during quenching, a finite element based approach was developed by coupling an iterative zone-based transient heat transfer algorithm with material thermo-viscoplastic constitutive model. With the integrated models, the numeric predictions of residual stresses and distortion in the quenched aluminum castings are in a good agreement with experimental measurements.

The spatial distribution of the mixture equivalence ratio within the squish volume is quantified under non-combusting conditions by planar laser-induced fluorescence (PLIF) of a fuel tracer (toluene). The measurements were made in a single-cylinder, direct-injection, light-duty diesel engine at conditions matched to an early-injection low temperature combustion mode. A fuel amount corresponding to a low load (3.0 bar indicated mean effective pressure) operating condition was introduced with a single injection. Data were acquired during the mixture preparation period from near the start of injection (-22.5° aTDC) until the crank angle where the start of high-temperature heat release normally occurs (-5° aTDC). Despite the opposing squish flow, the fuel jets penetrate through the squish region to the cylinder bore. Although rapid mixing is observed in the head of each jet, rich regions remain at the head at the start of high-temperature heat release.

General Motors' (GM) eAssist powertrain builds upon the knowledge and experience gained from GM's first generation 36Volt Belt-Alternator-Starter (BAS) system introduced on the Saturn VUE Green Line in 2006. Extensive architectural trade studies were conducted to define the eAssist system. The resulting architecture delivers approximately three times the peak electric boost and regenerative braking capability of 36V BAS. Key elements include a water-cooled induction motor/generator (MG), an accessory drive with a coupled dual tensioner system, air cooled power electronics integrated with a 115V lithium-ion battery pack, a direct-injection 2.4 liter 4-cylinder gasoline engine, and a modified 6-speed automatic transmission. The torque-based control system of the eAssist powertrain was designed to be fully integrated with GM's corporate common electrical and controls architectures, enabling the potential for broad application across GM's global product portfolio.