Search Results

A simulation framework with a validated system model capable of estimating fuel consumption is a valuable tool in analysis and design of the hybrid vehicles. In particular, the framework can be used for (1) benchmarking the fuel economy achievable from alternate hybrid powertrain technologies, (2) investigating sensitivity of fuel savings with respect to design parameters (for example, component sizing), and (3) evaluating the performance of various supervisory control algorithms for energy management. Presenter Chinmaya Patil, Eaton Corporation

The current simulation models of EV and ICE Vehicles are well known in industry for their use in estimating the fuel economy or Range benefits because of controller calibrations and component sizing. However, there is a gap in understanding the behavior of accessories such as HVAC, power steering and other such auxiliary loads and the energy losses associated with them. Impact of thermal behavior of electronics on vehicle range also needs to be studied in detail. These kinds of studies help OEM and tier 1 manufactures in improving their design concepts significantly with minimum cost and development time. Hence, the focus of this study is on building simulation models of thermal, electrical, traction and control circuits of a typical electric vehicle. These models are then integrated, and analysis is performed to understand vehicle system level performance metrics.

Diesel Cylinder Deactivation (CDA) has been shown in previous work to increase exhaust temperatures, improve fuel efficiency, and reduce engine-out NOx for engine loads up to 3 bar BMEP. The purpose of this study is to determine whether or not the turbocharger needs to be altered when implementing CDA on a diesel engine. This study investigates the effect of CDA on exhaust temperature, fuel efficiency, and turbocharger performance in a 15L heavy-duty diesel engine under low-load (0-3 bar BMEP) steady-state operating conditions. Two calibration strategies were evaluated. First, a “stay-hot” thermal management strategy in which CDA was used to increase exhaust temperature and reduce fuel consumption. Next, a “get-hot” strategy where CDA and elevated idle speed was used to increase exhaust temperature and exhaust enthalpy for rapid aftertreatment warm-up.

The most common and lethal weapons against military vehicles are the improvised explosive devices (IEDs). In an explosion, critical cabin’s penetrations and high accelerations can cause serious injuries and death of military personnel. This investigation uses single and multi-fidelity Bayesian optimization (BO) to design sandwich composite armors for blast mitigation. BO is an efficient methodology to solve optimization problems that involve black-box functions. The black-box function of this work is the finite element (FE) simulation of the armor subjected to blast. The main two components of BO are the surrogate model of the black-box function and the acquisition function that guides the optimization. In this investigation, the surrogate models are Gaussian Process (GP) regression models and the acquisition function is the multi-objective expected improvement (MEI) function. Information from low and high fidelity FE models is used to train the GP surrogates.

Global environmental and economic concerns regarding increasing fuel consumption and greenhouse gas emission are driving changes to legislative regulations and consumer demand. As regulations become more stringent, advanced engine technologies must be developed and implemented to realize desired benefits. Discrete variable valve lift technology is a targeted means to achieve improved fuel economy in gasoline engines. By limiting intake air flow with an engine valve, as opposed to standard throttling, road-load pumping losses are reduced resulting in improved fuel economy. This paper focuses on the design and development of a switching roller finger follower system which enables two mode discrete variable valve lift on end pivot roller finger follower valvetrains. The system configuration presented includes a four-cylinder passenger car engine with an electro-hydraulic oil control valve, dual feed hydraulic lash adjuster, and switching roller finger follower.

Excessive vibration and poor controllability occur in many mobile fluid power applications, with negative consequences as concerns operators' health and comfort as well as machine safety and productivity. This paper addresses the problem of reducing oscillations in fluid power machines presenting a novel control technique of general applicability. Strong nonlinearities of hydraulic systems and the unpredictable operating conditions of the specific application (e.g. uneven ground, varying loads, etc.) are the main challenges to the development of satisfactory general vibration damping methods. The state of the art methods are typically designed as a function of the specific application, and in many cases they introduce energy dissipation and/or system slowdown. This paper contributes to this research by introducing an energy efficient active damping method based on feedback signals from pressure sensors mounted on the flow control valve block.

The optimal design of hybrid-electric vehicle power systems poses a challenge to the system analyst, who is presented with a host of parameters to fine-tune, along with stringent performance criteria and multiple design objectives to meet. Herein, a methodology is presented to transform such a design task into a constrained multi-objective optimization problem, which is solved using a distributed evolutionary algorithm. A power system model representative of a series hybrid-electric vehicle is considered as a paradigm to support the illustration of the proposed methodology, with particular emphasis on the power system's time-domain performance.

ADVISOR is a flexible drivetrain analysis tool, developed in MATLAB/Simulink® to compare fuel economy and emissions performance between different drivetrain configurations. This paper reports a couple of numerical issues with application of ADVISOR 2002 to commercial vehicles with traditional powertrain systems. One instance is when ADVISOR model is set up to simulate running a heavy-duty (HD) truck with an automated manual transmission (AMT) on a demanding pickup-delivery duty cycle. The other is highlighted during an analysis of a medium-duty (MD) truck with an automatic transmission (AT) where wide-open throttle, i.e., fast acceleration is requested. These two cases have shown different numerical difficulties by using ADVISOR 2002. Based on studying the details of the models, solutions to these numerical issues are developed. The simulation results will demonstrate the effectiveness of these solutions.

Eaton has developed a prototype hydraulic hybrid vehicle energy management system that substantially improves fuel economy and reduces harmful emissions. The system was developed cooperatively with the U.S. Environmental Protection Agency (EPA), Navistar Inc., and the U.S. Army. The system has demonstrated fuel economy improvements in real world use of up to 50 percent while simultaneously reducing carbon emissions by up to 30 percent. The first real world application of the technology will be in parcel delivery vehicles owned by United Parcel Service (UPS). The hybrid vehicle energy management system components will be described and principles of operation explained. Major properties of the system will be examined and it will be shown why the hydraulic hybrid system is well suited for the parcel delivery vehicle application. Several secondary beneficial properties of the system will also be discussed.

The need for greater capacity in automotive transportation (in the midst of constrained resources) and the convergence of key technologies from multiple domains may eventually produce the emergence of a “swarm” concept of operations. The swarm, a collection of vehicles traveling at high speeds and in close proximity, will require management techniques to ensure safe, efficient, and reliable vehicle interactions. We propose a shared-autonomy approach in which the strengths of both human drivers and machines are employed in concert for this management. A fuzzy logic-based control implementation is combined with a genetic algorithm to select the shared-autonomy architecture and sensor capabilities that optimize swarm operations.

The Mississippi State University Formula SAE race car upright was optimized using radial basis function metamodels and an internal state variable (ISV) plasticity damage material model. The weight reduction of the upright was part of a goal to reduce the weight of the vehicle by 25 percent. Using an optimization routine provided an upright design that is lighter that helps to improve vehicle fuel economy, acceleration, and handling. Finite element (FE) models of the upright were produced using quadratic tetrahedral elements. Using tetrahedral elements provided a quick way to produce the multiple FE models of the upright required for the multi-objective optimization. A design of experiments was used to determine how many simulations were required for the optimization. The loads for the simulations included braking, acceleration, and corning loads seen by the car under track conditions.

Eaton has developed a prototype hydraulic hybrid vehicle energy management system that substantially improves fuel economy and reduces harmful emissions. The system was developed cooperatively with the U.S. Environmental Protection Agency (EPA), Navistar Inc., and the U.S. Army. The system has demonstrated fuel economy improvements in real world use of up to 50 percent while simultaneously reducing carbon emissions by up to 30 percent. The first real world application of the technology will be in parcel delivery vehicles owned by United Parcel Service (UPS). The hybrid vehicle energy management system components will be described and principles of operation explained. Major properties of the system will be examined and it will be shown why the hydraulic hybrid system is well suited for the parcel delivery vehicle application. Several secondary beneficial properties of the system will also be discussed.

This paper describes the numerical modeling of the hydraulic circuit of a self-moving boom lift. Boom lifts consist of several hydraulic actuators, each of them performs a specific movement. Hydraulic systems for lifting applications must ensure consistent performance no matter what the load and how many users are in operation at the same time. Common solutions comprise a fixed or a variable displacement pump with load-sensing control strategy. Instead, the hydraulic circuit studied in this paper includes a fixed displacement pump and an innovative (patented) proportional valve assembly. Each proportional valve (one for each user) permits a flow regulation for all typical load conditions and movement simultaneously. The study of the hydraulic system required a detailed modeling of some components such as: the overcenter valves, for the control of the assistive loads; the proportional valve, which keeps a constant flow independently of pressure drop across itself.

The power management control system development and vehicle test results for a medium-duty hybrid electric truck are reported in this paper. The design procedure adopted is a model-based approach, and is based on the dynamic programming technique. A vehicle model is first developed, and the optimal control actions to maximize fuel economy are then obtained by the dynamic programming method. A near-optimal control strategy is subsequently extracted and implemented using a rapid-prototyping control development system, which provides a convenient environment to adjust the control algorithms and accommodate various I/O configurations. Dynamometer-testing results confirm that the proposed algorithm helps the prototype hybrid truck to achieve a 45% fuel economy improvement on the benchmark (non-hybrid) vehicle. It also compares favorably to a conventional rule-based control method, which only achieves a 31% fuel economy improvement on the same hybrid vehicle.

Pick up and delivery vehicle applications such as parcel handling trucks represent an ideal duty cycle for Hybrid Electric Powertrains. The low speed, frequent stopping and starting operation provides good opportunities for enhancing engine behavior and recovering braking energy by adding an electric drive system to the vehicle. FedEx Express collaborated with the environmental advocacy group Environmental Defense to announce the Future Vehicle Program, with the goal of developing significant improvements in emissions and fuel economy for the familiar FedEx Express W700 parcel delivery vehicle. This paper describes the objectives, development activities, and test results for one of the vehicles submitted to this program. A team led by Eaton Corporation prepared the Direct Hybrid Electric Powertrain system, which received the highest ranking in the Future Vehicle Program evaluation.

A methodology for modeling elastomeric mounts as nonlinear lumped parameter models is discussed. A key feature of this methodology is that it integrates dynamic test results under different conditions into the model. The first step is to model the mount as a linear model that is simple but reproduces accurately results from dynamic tests under small excitations. Frequency Response Functions (FRF) enables systematic calculation of the parameters for the model. Under more realistic excitation, the mount exhibits non-linearity, which is investigated in the next step. For nonlinear structures, a simple and intuitive method is to use time-domain force-displacement (F-x) curves. Experiments to obtain the F-x curves involve controlling the displacement excitation and measuring the induced forces. From the F-x curves, stiffness and damping parameters are obtained with an optimization technique.

This paper presents the continuation of the modeling work described in a companion paper “Modeling of Nonlinear Elastomeric Mounts. Part 1: Dynamic Testing and Parameter Identification” by the same authors. That paper discussed a dynamic test procedure and an optimization methodology to identify and model an elastomeric mount as a non-linear lumped parameter structure. This paper discusses a numerical modeling methodology to confirm or improve the agreement between the dynamic test results and the input-output relationship of the analytical model generated in the companion paper. In this paper, the model developed in the companion paper and the model parameters are input into a dynamic simulation model using a commercial simulation package. The model is then run to produce the numerical force-versus-displacement (F-x) curves of the mount. The numerical F-x curves are compared with the F-x curves obtained from the experiments.

In this paper, an aggregate system level modeling and analysis framework is proposed to facilitate the integration and design of advanced life support systems (ALSS). As in process design, the goal is to choose values for the degrees of freedom that achieve the best overall ALSS behavior without violating any system constraints. At the most fundamental level, this effort will identify the constraints and degrees of freedom associated with each subsystem and provide estimates of the system behavior and interactions involved in ALSS. This work is intended to be a starting point for developing insights into ALSS from a systems engineering point of view. At this level, simple aggregate static input/output mapping subsystem models from existing data and the NASA ALS BVAD document are used to debug the model and demonstrate feasibility.

An important function of life support systems developed for a long duration human mission to Mars is the ability to recycle water and air. The Bio-Regenerative Environmental Air Treatment for Health (BREATHe) is part of a multicomponent life support system and will simultaneously treat wastewater and air. The BREATHe system will consist of packed bed biofilm reactors. Model waste streams will be used for experiments conducted during the design phase of the BREATHe system. This paper summarizes expected characteristics of water and air waste steams that would be generated by a crew of six during a human mission to Mars. In addition to waste air and water generation rates, the chemical composition of each waste stream is defined. Specifically, chemical constituents expected to be present in hygiene wastewater, dishwater, laundry water, atmospheric condensate, and cabin air are presented.

A special vehicle dynamometer has been developed that allows engineers to evaluate driveline components and control algorithms for advanced, electrically-assisted drive systems on commercial vehicles. This dynamometer allows objective measurements of performance, fuel economy, and exhaust emissions, while the full vehicle is operated over a specified driving cycle. This system can be used to exercise the electric motor, engine, transmission and battery systems on Medium Duty Hybrid Trucks - in regeneration as well as power mode - all indoors and in a controlled, repeatable environment. This paper will provide descriptions of the operating goals, control features, and results of testing with this dynamometer. Once the various parameters have been optimized for fuel and emissions performance in this facility, the vehicle can be evaluated where it counts - on the road.