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Warranty forecasting of repairable systems is very important for manufacturers of mass produced systems. It is desired to predict the Expected Number of Failures (ENF) after a censoring time using collected failure data before the censoring time. Moreover, systems may be produced with a defective component resulting in extensive warranty costs even after the defective component is detected and replaced with a new design. In this paper, we present a forecasting method to predict the ENF of a repairable system using observed data which is used to calibrate a Generalized Renewal Processes (GRP) model. Manufacturing of products may exhibit different production patterns with different failure statistics through time. For example, vehicles produced in different months may have different failure intensities because of supply chain differences or different skills of production workers, for example.

Heavy-duty diesel engine particulate matter (PM) emissions must be reduced from 0.1 to 0.01 grams per brake horsepower-hour by 2007 due to EPA regulations [1]. A catalyzed particulate filter (CPF) is used to capture PM in the exhaust stream, but as PM accumulates in the CPF, exhaust flow is restricted resulting in reduced horsepower and increased fuel consumption. PM must therefore be burned off, referred to as CPF regeneration. Unfortunately, nominal exhaust temperatures are not always high enough to cause stable self-regeneration when needed. One promising method for active CPF regeneration is to inject fuel into the exhaust stream upstream of an oxidation catalytic converter (OCC). The chemical energy released during the oxidation of the fuel in the OCC raises the exhaust temperature and allows regeneration.

Improving vehicle response through advanced knowledge of traffic behavior can lead to large improvements in energy consumption for the single isolated vehicle. This energy savings across multiple vehicles can even be larger if they travel together as a cohort in harmonization. Additionally, if the vehicles have enough information about their immediate path of travel, and other vehicles’ in that path (and their respective critical forward-looking information), they can safely drive close enough to each other to share aerodynamic load. These energy savings can be upwards of multiple percentage points, and are dependent on several criteria. This analysis looks at criteria that contributes to energy savings for a cohort of vehicles in synchronous motion, as well as describes a study that allows for better understanding of the potential benefits of different types of cohorted vehicles in different platoon arrangements.

Numerical modeling of fuel injection in internal combustion engines in a Lagrangian framework requires the use of a spray-wall interaction sub-model to correctly assess the effects associated with spray impingement. The spray impingement dynamics may influence the air-fuel mixing and result in increased hydrocarbon and particulate matter emissions. One component of a spray-wall interaction model is the splashed mass fraction, i.e. the amount of mass that is ejected upon impingement. Many existing models are based on relatively large droplets (mm size), while diesel and gasoline sprays are expected to be of micron size before splashing under high pressure conditions. It is challenging to experimentally distinguish pre- from post-impinged spray droplets, leading to difficulty in model validation.

Robust autonomous navigation in unstructured environments is an unsolved problem and critical to the operation of autonomous military and rescue ground vehicles. Two-dimensional path planners operating on occupancy grids or costs maps can produce infeasible paths when the operational area includes complex terrain. Recently, sample-based path planners that plan on LiDAR-acquired point-cloud maps have been proposed. These approaches require no discretization of the operational area and provide direct pose estimation by modeling vehicle and terrain interaction. In this paper, we show that direct sample-based path planning on point clouds is effective and robust in unstructured environments. Robustness is demonstrated by completing a system parameter sensitivity analysis of the system in an Unreal simulation environment and partnered with field validation.

We have recently obtained experimental data and used them to develop computational models to quantify occupant impact responses and injury risks for military vehicles during frontal crashes. The number of experimental tests and model runs are however, relatively small due to their high cost. While this is true across the auto industry, it is particularly critical for the Army and other government agencies operating under tight budget constraints. In this study we investigate through statistical simulations how the injury risk varies if a large number of experimental tests were conducted. We show that the injury risk distribution is skewed to the right implying that, although most physical tests result in a small injury risk, there are occasional physical tests for which the injury risk is extremely large. We compute the probabilities of such events and use them to identify optimum design conditions to minimize such probabilities.

This paper presents a Short Time Fourier Transform based algorithm to identify unknown parameters in fuel dynamics system during engine cold start and warm-up. A first order system is used to model the fuel dynamics in a port fuel injection engine. The feed forward transient fuel compensation controller is designed based on the identified model. Experiments are designed and implemented to verify the proposed algorithm. Different experiment settings are compared.

While significant progress has been made in recent years to develop hybrid and battery electric vehicles for passenger car and light-duty applications to meet future fuel economy targets, the application of hybrid powertrains to heavy-duty truck applications has been very limited. The relatively lower energy and power density of batteries in comparison to diesel fuel and the operating profiles of most heavy-duty trucks, combine to make the application of hybrid powertrain for these applications more challenging. The high torque and power requirements of heavy-duty trucks over a long operating range, the majority of which is at constant cruise point, along with a high payback period, complexity, cost, weight and range anxiety, make the hybrid and battery electric solution less attractive than a conventional powertrain.

Recent developments in time-dependent reliability have introduced the concept of a composite limit state. The composite limit state method can be used to calculate the time-dependent probability of failure for dynamic systems with limit-state functions of input random variables, input random processes and explicit in time. The probability of failure can be calculated exactly using the composite limit state if the instantaneous limit states are linear, forming an open or close polytope, and are functions of only two random variables. In this work, the restriction on the number of random variables is lifted. The proposed algorithm is accurate and efficient for linear instantaneous limit state functions of any number of random variables. An example on the design of a hydrokinetic turbine blade under time-dependent river flow load demonstrates the accuracy of the proposed general composite limit state approach.

The Vehicle Engine Cooling System Simulation (VECSS) computer code has been developed at the Michigan Technological University to simulate the thermal response of the cooling system of an on-highway heavy duty diesel powered truck under steady and transient operation. This code includes an engine cycle analysis program along with various components for the four main fluid circuits for cooling air, cooling water, cooling oil, and intake air, all evaluated simultaneously. The code predicts the operation of the response of the cooling circuit, oil circuit, and the engine compartment air flow when the VECSS is operated using driving cycle data of vehicle speed, engine speed, and fuel flow rate for a given ambient temperature, pressure and relative humidity.

A one-dimensional incompressible flow model covering the mechanisms involved in the airflow through an automotive radiator-shroud-fan system with no heat transfer was developed. An analytical expression to approximate the experimentally determined fan performance characteristics was used in conjunction with an analytical approach for this simplified cooling airflow model, and the solution is discussed with illustrations. A major result of this model is a closed form equation relating the transient velocity of the air to the vehicle speed, pressure rise characteristics and speed of the fan, as well as the dimensions and resistance of the radiator. This provides a basis for calculating cooling airflow rate under various conditions. The results of the incompressible flow analysis were further compared with the computational results obtained with a previously developed one-dimensional, transient, compressible flow model.

This paper studies the hardware-in-the-loop (HiL) design of a power-split hybrid electric vehicle (HEV) for the research of HEV lithiumion battery aging. In this paper, an electrochemical model of a lithium-ion battery pack with the characteristics of battery aging is built and integrated into the vehicle model of Autonomie® software from Argonne National Laboratory. The vehicle model, together with the electrochemical battery model, is designed to run in a dSPACE real-time simulator while the powertrain power distribution is managed by a dSPACE MicroAutoBoxII hardware controller. The control interface is designed using dSPACE ControlDesk to monitor the real-time simulation results. The HiL simulation results with the performance of vehicle dynamics and the thermal aging of the battery are presented and analyzed.

Lean limit characteristics of a pneumatic port fuel injection system is compared to a conventional port fuel injection system. The lean limit was based on the measured peak pressure. Those cycles with peak pressures greater than 105 % of the peak pressure for a nonfiring cycle were counted. Experimental data suggests that there are differences in lean limit characteristics between the two systems studied, indicating that fuel preparation processes in these systems influence the lean limit behaviors. Lean limits are generally richer for pneumatic fuel injection than those for conventional fuel injection. At richer fuel-to-air ratios the pneumatic injector usually resulted in higher torques. A simple model to estimate the evaporation occurring in the inlet manifold provided an explanation for the observed data.

The U.S. Army currently uses JP-8 for global operations according to the "one fuel forward policy" that was enacted almost twenty years ago in order to help reduce the logistics burden of supplying a variety of fuels for given Department of Defense vehicle and base applications. One particular challenge with using global JP-8 is the lack of or too broad a range of specified combustion and fuel system affecting properties including ignition quality, high temperature viscosity, and lubricity. In addition to these challenges, the JP-8 fuel specification currently allows the use of blending with certain types of synthetic jet fuels up to 50% by volume. This blended fuel also doesn't include an ignition quality or high temperature viscosity specification, but does include a lubricity specification that is much less restrictive than DF-2.

Active regeneration of a catalyzed particulate filter (CPF) is affected by a number of parameters specifically particulate matter loading and inlet temperature. The MTU 1-D 2-Layer CPF model [1] was used to analyze these effects on the pressure drop, oxidation and filtration characteristics of a CPF during active regeneration. In addition, modeling results for post loading experiments were analyzed to understand the difference between loading a clean filter as compared to a partially regenerated filter. Experimental data obtained with a production Cummins regenerative particulate filter for loading, active regenerations and post loading experiments were used to calibrate the MTU 1-D 2-Layer CPF model. The model predicted results are compared with the experimental data and were analyzed to understand the CPF characteristics during active regeneration at 1.1, 2.2 and 4.1 g/L particulate matter (PM) loading and CPF inlet temperatures of 525, 550 and 600°C.

A 1-D 2-layer model developed previously at MTU was used in this research to predict the pressure drop, filtration characteristics and various properties of the particulate filter and the particulate deposit layer. The model was calibrated and validated for this CPF with data obtained from steady state experiments conducted using a 1995 Cummins M11-330E heavy-duty diesel engine with manual EGR and using ULSF. The CPF used is a NGK filter having a cordierite substrate with NEX catalyst type formulation (54% porosity, 15.0 μm mean pore diameter and 50 gms/ft3 Pt). The filter was catalyzed using a wash coat process. The model was used to predict the pressure drop, particulate mass retained inside the CPF, particulate mass filtration efficiency and concentration downstream of the CPF with agreement between the experimental and simulated data.

Physical, chemical, and biological characterization data for the particulate emissions from a Caterpillar 3208 diesel engine with and without Corning porous ceramic particulate traps are presented. Measurements made at EPA modes 3,4,5,9,lO and 11 include total hydrocarbon, oxides of nitrogen and total particulate matter emissions including the solid fraction (SOL), soluble organic fraction (SOF) and sulfate fraction (SO4), Chemical character was defined by fractionation of the SOF while biological character was defined by analysis of Ames Salmonella/ microsome bioassay data. The trap produced a wide range of total particulate reduction efficiencies (0-97%) depending on the character of the particulate. The chemical character of the SOF was significantly changed through the trap as was the biological character. The mutagenic specific activity of the SOF was generally increased through the trap but this was offset by a decrease in SOF mass emissions.

The objective of this research was to study the effect of a catalyzed particulate filter (CPF) with a high loading of catalyst (50 gms/ft3) and ultra low sulfur fuel (ULSF -0.57 ppm of sulfur) on the emissions from a heavy duty diesel engine. The particulate emissions were measured using two different analytical methods, i.e., the gravimetric method and the thermal optical method (TOM). The results from the two different methods of analyses were compared. The experiments were performed at four different operating conditions chosen from the old Environmental Protection Agency (EPA) 13-mode test cycle. A 1995 Cummins M11 heavy-duty engine with manually controlled exhaust gas recirculation (EGR) was used to perform the emission characterization experiments. The emission characterization included total particulate matter (TPM), which is composed of the solids (SOL), soluble organic fractions (SOF) and sulfates (SO4) analyzed using the gravimetric method.

A 1-D 2-layer model developed previously at MTU was used in this research to predict the pressure drop, filtration characteristics and various properties of the particulate filter and the particulate deposit layer. The model was used along with dilute emission data to characterize two catalyzed particulate filters (CPFs) having different catalyst loading and catalyst application processes. The model was calibrated and validated with data obtained from steady state experiments conducted using a 1995 Cummins M11-330E heavy-duty diesel engine with manual EGR with different fuels for the two different CPFs. The two different catalyzed particulate filters were CPF III (5 gms/ft3 Pt) and CPF V (50 gms/ft3 Pt). Both the CPFs had cordierite substrates with CPF III and CPF V had MEX and NEX catalyst type formulation respectively. The CPF III filter was catalyzed using a solution-impregnated process while the CPF V filter was catalyzed using a wash coat process.

Elastomers are traditionally designed for use in applications that require specific mechanical properties. Unfortunately, these properties change with respect to many different variables including heat, light, fatigue, oxygen, ozone, and the catalytic effects of trace elements. When elastomeric mounts are designed for NVH use in vehicles, they are designed to isolate specific unwanted frequencies. As the elastomers age however, the desired elastomeric properties may have changed with time. This study looks at the variability seen in new vehicle engine mounts and how the dynamic properties change with respect to miles accumulated on fleet and durability test vehicles.