Search Results

Ride control of military vehicles is challenging due to varied terrain and mission requirements such as operating weight. Achieving top speeds on rough terrain is typically considered a key performance parameter, which is always constrained by ride discomfort. Many military vehicles using passive suspensions suffer with compromised performance due to single tuning solution. To further stretch the performance domain to achieving higher speeds on rough roads, semi-active suspensions may offer a wide range of damping possibilities under varying conditions. In this paper, various semi-active control strategies are examined, and improvements have been made, particularly, to the acceleration-driven damper (ADD) strategy to make the approach more robust for varying operating conditions. A seven degrees of freedom ride model and a quarter-car model were developed that were excited by a random road process input modeled using an auto-regressive time series model.

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.

This research paper addresses the ground vehicle reliability prediction process based on a new integrated reliability prediction framework. The integrated stochastic framework combines the computational physics-based predictions with experimental testing information for assessing vehicle reliability. The integrated reliability prediction approach incorporates the following computational steps: i) simulation of stochastic operational environment, ii) vehicle multi-body dynamics analysis, iii) stress prediction in subsystems and components, iv) stochastic progressive damage analysis, and v) component life prediction, including the effects of maintenance and, finally, iv) reliability prediction at component and system level. To solve efficiently and accurately the challenges coming from large-size computational mechanics models and high-dimensional stochastic spaces, a HPC simulation-based approach to the reliability problem was implemented.

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.

For existing fleets such as the U.S. military ground vehicle fleet, there are few ways to reduce vehicle fuel consumption that don’t involve expensive retrofitting. Replacing standard lubricants with those that can achieve higher vehicle efficiencies is one practical and inexpensive way to improve fleet fuel efficiency. In an effort to identify axle gear lubricants that can reduce the fuel consumption of its fleet, the U.S. Army is developing a stationary axle efficiency test stand and procedure. In order to develop this capability, on-track vehicle fuel consumption testing was completed using light, medium, and heavy tactical wheeled vehicles following a modified SAE J1321 type test procedure. Tested lubricants included a baseline SAE 80W-90, a fuel efficient SAE 75W-90, and a fuel efficient SAE 75W-140. Vehicle testing resulted in reductions in fuel consumption of up to 2%.

Vehicle operation during cold-start powertrain conditions can have a significant impact on drivability, fuel economy and tailpipe emissions in modern passenger vehicles. As efforts continue to maximize fuel economy in passenger vehicles, considerable engineering resources are being spent in order to reduce the consumption penalties incurred shortly after engine start and during powertrain warmup while maintaining suitably low levels of tailpipe emissions. Engine downsizing, advanced transmissions and hybrid-electric architecture can each have an appreciable effect on cold-start strategy and its impact on fuel economy. This work seeks to explore the cold-start strategy of several passenger vehicles with different powertrain architectures and to understand the resulting fuel economy impact relative to warm powertrain operation. To this end, four vehicles were chosen with different powertrain architectures.

One-dimensional simulation methods for unsteady (transient) engine operations have been developed and published in previous studies. These 1-D methods utilize heat release and emissions results obtained from 3-D CFD simulations which are stored in a data library. The goal of this study is to improve the 1-D methodology by optimizing the control strategies. Also, additional independent parameters are introduced to extend the 3-D data library, while, as in the previous studies, the number of interpolation points for each parameter remains small. The data points for the 3-D simulations are selected in the vicinity of the expected trajectories obtained from the independent parameter changes, as predicted by the transient 1-D simulations. By this approach, the number of time-consuming 3-D simulations is limited to a reasonable amount.

Exhaust gas recirculation (EGR) has been employed in a diesel engine to reduce NOx emissions by diluting the fresh air charge with gases composed of primarily N2, CO2, H2O, and O2 from the engines exhaust stream. The addition of EGR reduces the production of NOx by lowering the peak cylinder gas temperature and reducing the concentration of O2 molecules, both of which contribute to the NOx formation mechanism. The amount of EGR has been typically controlled using an open loop control strategy where the flow of EGR was calibrated to the engine speed and load and controlled by the combination of an EGR valve and the ratio of the boost and exhaust back pressures. When oxygenated biofuels with lower specific energy are used, the engine control unit (ECU) will demand a higher fuel rate to maintain power output, which can alter the volumetric flow rate of EGR. In addition, oxygenated biofuels affect the oxygen concentration in the intake manifold gas stream.

Real-time driving simulations are an important tool for verifying vehicle and vehicle component designs with a driver in the loop. They not only provide a cost effective solution but also an ability to verify designs in a safe and controlled operating environment. A real-time driving experiment has been developed for Stryker to compare the ride and handling performance of a baseline passive suspension to that of a Magneto-Rheological (MR) semi-active damper suspension. The Tank Automotive Research Development and Engineering Center (TARDEC) has integrated this new suspension into a real time vehicle dynamics model of the Stryker using the MR suspension model developed by the Original Equipment Manufacturer (OEM). Using this real-time model and the TARDEC Ride Motion Simulator (RMS), TARDEC associates, along with associates from the Stryker Program Management office and the suspension OEM were able to drive and compare the passive and MR Stryker in a virtual environment.

Military vehicles are typically armored, hence the open surface area for heat rejection is limited. Hence, the cooling parasitic load for a given heat rejection can be considerably higher and important to consider upfront in the system design. Since PEMFCs operate at low temp, the required cooling flow is larger to account for the smaller delta temperature to the air. This research aims to address the combined problem of optimal sizing of the lithium ion battery and PEM Fuel Cell stack along with development of the scalable power split strategy for small a PackBot robot. We will apply scalable physics-based models of the fuel cell stack and balance of plant that includes a realistic and scalable parasitic load from cooling integrated with existing scalable models of the lithium ion battery. This model allows the combined optimization that captures the dominant trends relevant to component sizing and system performance.

Precise cycle-to-cycle control of combustion is the major challenge to reduce fuel consumption in Homogenous Charge Compression Ignition (HCCI) engines, while maintaining low emission levels. This paper outlines a framework for simultaneous control of HCCI combustion phasing and Indicated Mean Effective Pressure (IMEP) on a cycle-to-cycle basis. A dynamic control model is extended to predict behavior of HCCI engine by capturing main physical processes through an HCCI engine cycle. Performance of the model is validated by comparison with the experimental data from a single cylinder Ricardo engine. For 60 different steady state and transient HCCI conditions, the model predicts the combustion phasing and IMEP with average errors less than 1.4 CAD and 0.2 bar respectively. A two-input two-output controller is designed to control combustion phasing and IMEP by adjusting fuel equivalence ratio and blending ratio of two Primary Reference Fuels (PRFs).

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 fuel injection pressure and the swirl motion have a great impact on combustion in small bore HSDI diesel engines running on the conventional or advanced combustion concepts. This paper examines the effects of injection pressure and the swirl motion on engine-out emissions over a wide range of EGR rates. Experiments were conducted on a single cylinder, 4-valve, direct injection diesel engine equipped with a common rail injection system. The pressures and temperatures in the inlet and exhaust surge tanks were adjusted to simulate turbocharged engine conditions. The load and speed of the engine were typical to highway cruising operation of a light duty vehicle. The experiments covered a wide range of injection pressures, swirl ratios and injection timings. Engine-out emission measurements included hydrocarbons, carbon monoxide, smoke (in Bosch Smoke Units, BSU) and NOx.

Aluminum based brake rotors have been a priority research topic in the DOE 1999 Aluminum Industry Roadmap for the Automobile Market. After fourteen years, no satisfactory technology has been developed to solve the problem of aluminum's low working temperatures except the steel clad aluminum (SCA) brake technology. This technology research started at Michigan Technological University (MTU) in 2001 and has matured recently for commercial productions. The SCA brake rotor has a solid body and replaces the traditional convective cooling of a vented rotor with conductive cooling to a connected aluminum wheel. Much lower temperatures result with the aluminum wheel acting as a great heat sink/radiator. The steel cladding further increases the capability of the SCA rotor to withstand higher surface temperatures. During the road tests of SCA rotors on three cars, significant gas mileage improvement was found; primarily attributed to the unique capability of the SCA rotor on pad drag reduction.

This paper discusses the evaluation and application of a portable parked-vehicle tailpipe emissions measurement apparatus (EMA). The EMA consists of an exhaust dilution system and a portable instrument package. The EMA instantaneously dilutes and cools a sample of exhaust with compressed nitrogen or air at a known dilution ratio, thereby presenting it to instruments as it is presented to personnel in the surrounding environment. The operating principles and governing equations of the EMA are presented. A computational method is presented to determine the engine operating and performance parameters from the exhaust CO2 concentrations along with an assumed engine overall volumetric efficiency and brake specific fuel consumption. The parameters determined are fuel/air ratio, mass flow rates of fuel, air and exhaust emissions, and engine brake torque and horsepower.

Experimental Brake Specific Fuel Consumption (BSFC) data are presented for two engines as a function of engine speed, load, outlet coolant temperature and inlet oil temperature. The engines used in the study were the Cummins VT-903 (turbocharged) and the Caterpillar 3208, both being direct-injection and four-cycle. The data were taken for the Cat 3208 engine using a fractional factorial statistical method which reduced the total test matrix from 256 to 64 data points. The experimental data are used in the development of BSFC regression equations as a function of load, speed, outlet coolant temperature and inlet oil temperatures. A mathematical parameter for expressing quantitatively the change of BSFC per 10°F change in coolant and oil temperature is presented. It was found that an increase in the coolant and/or oil temperatures had the effect of reducing BSFC in both engines.

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.

Vehicles with power exporting capability are microgrids since they possess electrical power generation, onboard loads, energy storage, and the ability to interconnect. The unique load and silent watch requirements of some military vehicles make them particularly well-suited to augment stationary power grids to increase power resiliency and capability. Connecting multiple vehicles in a peer-to-peer arrangement or to a stationary grid requires scalable power management strategies to accommodate the possibly large numbers of assets. This paper describes a military ground vehicle power management scheme for vehicle-to-grid applications. The particular focus is overall fuel consumption reduction of the mixed asset inventory of military vehicles with diesel generators typically used in small unit outposts.

The ability to operate a spark-ignition (SI) engine near the knock limit provides a net reduction of engine fuel consumption. This work presents a real-time knock control system based on stochastic knock detection (SKD) algorithm. The real-time stochastic knock control (SKC) system is developed in MATLAB Simulink, and the SKC software is integrated with the production engine control strategy through ATI's No-Hooks. The SKC system collects the stochastic knock information and estimates the knock level based on the distribution of knock intensities fitting to a log-normal (LN) distribution. A desired knock level reference table is created under various engine speeds and loads, which allows the SKC to adapt to changing engine operating conditions. In SKC system, knock factor (KF) is an indicator of the knock intensity level. The KF is estimated by a weighted discrete FIR filter in real-time.

This investigation focuses on conventional powertrain technologies that provide operational synergy based on customer utilization to reduce fuel consumption for a heavy-duty, nonroad (off-road) material handler. The vehicle of interest is a Pettibone Cary-Lift 204i, with a base weight of 50,000 lbs. and a lift capacity of 20,000 lbs. The conventional powertrain consists of a US Tier 4 Final diesel engine, a non-lockup torque converter, a four-speed powershift automatic transmission, and all-wheel drive. The paper will present a base vehicle energy/fuel consumption breakdown of propulsion, hydraulic and idle distribution based on a representative end-user drive cycle. The baseline vehicle test data was then used to develop a correlated lumped parameter model of the vehicle-powertrain-hydraulic system that can be used to explore technology integration that can reduce fuel consumption.