Search Results

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 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.

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.

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.

Since the advent of P/M technology as a near net shape production process, millions of mechanical components of various shapes and sizes have been produced. Although P/M continues to be one of the fast growing shaping processes, it suffers from the inability to produce intricate geometry's such as internal tapers, threads or recesses perpendicular to pressing direction. In such cases application of machining as a secondary forming operation becomes the preferred alternative. However, machining of P/M parts due to their inherent porosity is known to decrease tool life and increase tool chatter and vibration. Consequently, several attempts have been made to improve the machinability of P/M materials by either addition of machinability enhancing elements such as sulfur, calcium, tellurium, selenium, etc., or by resin impregnation of P/M parts.

Engineering new technology and products challenges managers to balance design innovation and program risk. To do this, managers need methods to judge future results to avoid program and product disasters. Besides the traditional prediction tools of schedule, simulations and “iron tests”, process control standards (with measurements) can also be applied to the development programs to mitigate risks. This paper briefly discusses the theory and case history behind some new process control methods and standards currently in place at Caterpillar's Electrical & Electronics department. Process standards reviewed in this paper include process mapping, ISO9001, process controls, and process improvement models (e.g. SEI's CMMs.)

A global optimization method has been developed for an engine simulation code and utilized in the search of optimal fuel injection strategies. This method uses a Lagrange interpolation function which interpolates engine output data generated at the vertices and the intermediate points of the input parameters. This interpolation function is then used to find a global minimum over the entire parameter set, which in turn becomes the starting point of a CFD-based optimization. The CFD optimization is based on a steepest descent method with an adaptive cost function, where the line searches are performed with a fast-converging backtracking algorithm. The adaptive cost function is based on the penalty method, where the penalty coefficient is increased after every line search. The parameter space is normalized and, thus, the optimization occurs over the unit cube in higher-dimensional space.

Optimal fuel injection strategies are obtained with a micro-genetic algorithm and an adaptive gradient method for a nonroad, medium-speed DI diesel engine equipped with a multi-orifice, asynchronous fuel injection system. The gradient optimization utilizes a fast-converging backtracking algorithm and an adaptive cost function which is based on the penalty method, where the penalty coefficient is increased after every line search. The micro-genetic algorithm uses parameter combinations of the best two individuals in each generation until a local convergence is achieved, and then generates a random population to continue the global search. The optimizations have been performed for a two pulse fuel injection strategy where the optimization parameters are the injection timings and the nozzle orifice diameters.

The objective of this project was to model and study the interior noise in an Off-Highway Truck cab using Statistical Energy Analysis (SEA). The analysis was performed using two different modeling techniques. In the first method, the structural members of the cab were modeled along with the panels and the interior cavity. In the second method, the structural members were not modeled and only the acoustic cavity and panels were modeled. Comparison was done between the model with structural members and without structural members to evaluate the necessity of modeling the structure. Correlation between model prediction of interior sound pressure and test data was performed for eight different load conditions. Power contribution analysis was performed to find dominant paths and 1/3rd octave band frequencies.

Faced with competitive environments, pressure to lower development costs and aggressive timelines engineers are not only increasingly adopting numerical simulation techniques but are also embracing design optimization schemes to augment their efforts. These techniques not only provide more understanding of the trade-offs but are also capable of proactively guiding the decision making process. However, design optimization and exploration tools have struggled to find complete acceptance and are typically underutilized in many applications; especially in situations where the algorithms have to compete with existing swift decision making processes. In this paper we demonstrate how the type of setup and algorithmic choice can have an influence and make optimization more lucrative in a new product development atmosphere. We also present some results from a design exploration activity, involving linkage and structural development, of an earth moving machine application.

This paper analyzes the control of the series-parallel powersplit used in the 2001 Michigan Tech FutureTruck. An electronic throttle controller is implemented and a new control algorithm is proposed and tested. A vehicle simulation has been created in MATLAB and the control algorithm implemented within the simulation. A program written in C has also been created that implements the control algorithm in the test vehicle. The results from both the simulation and test vehicle are presented and discussed and show a 15% increase in fuel economy. With the increase in fuel economy, and through the use of the original exhaust after treatment, lower emissions are also expected.

This study investigates a methodology in which the general public's subjective interpretation of vehicle handling and performance can be predicted. Several vehicle handling measurements were acquired, and associated metrics calculated, in a controlled setting. Human evaluators were then asked to drive and evaluate each vehicle in a winter driving school setting. Using the acquired data, multiple linear regression and artificial neural network (ANN) techniques were used to create and refine mathematical models of human subjective responses. It is shown that artificial neural networks, which have been trained with the sets of objective and subjective data, are both more accurate and more robust than multiple linear regression models created from the same data.

Most of the history of systems engineering has been focused on processes for engineering a single complex system. However, most large enterprises design, manufacture, operate, sell, or support not one product but multiple product lines of related but varying systems. They seek to optimize time to market, costs of development and production, leverage of intellectual assets, best use of talented human resources, overall competitiveness, overall profitability and productivity. Optimizing globally across multiple product lines does not follow from treating each system family member as an independently engineered system or product. Traditional systems engineering principles can be generalized to apply to families. This article includes a multi-year case study of the actual use of a generic model-based systems engineering methodology for families, Systematica™, across the embedded electronic systems products of one of the world's largest manufacturers of heavy equipment.

A 2-dimensional numerical model (MTU-FILTER) for a single channel of a honeycomb ceramic diesel particulate trap has been developed. The mathematical modeling of the filtration, flow, heat transfer and regeneration behavior of the particulate trap is described. Numerical results for the pressure drop and particulate mass were compared with existing experimental results. Parametric studies of the diesel particulate trap were carried out. The effects of trap size and inlet temperature on the trap performance are studied using the trap model. An approximate 2-dimensional analytical solution to the simplified Navier-Stokes equations was used to calculate the velocity field of the exhaust flow in the inlet and outlet channels. Assuming a similarity velocity profile in the channels, the 2-dimensional Navier-Stokes equations are approximated by 1-dimenisonal conservation equations, which is similar to those first developed by Bissett.

Today’s business climate and economy demand new, innovative strategies from the initial kickoff of research and development - to the mining of ore from the earth - to the final inspection of a finished product in a mid-western factory. From startup companies with two employees to the largest companies, the world faces new and challenging requirements every day. The demands from companies, customers, executives, and shareholders continue to drive for higher outputs with more efficient use of personnel and investments. Fortunately, the rate of technology continues to exponentially accelerate, which allows those at the cutting edge of technology to capitalize. Caterpillar has been a pioneer in advanced technology since its inception and has been developing the foundation for autonomy over the past four decades.

Verification and validation (V&V) are essential stages in the design cycle of industrial controllers to remove the gap between the designed and implemented controller. In this study, a model-based adaptive methodology is proposed to enable easily verifiable controller design based on the formulation of a sliding mode controller (SMC). The proposed adaptive SMC improves the controller robustness against major implementation imprecisions including sampling and quantization. The application of the proposed technique is demonstrated on the engine cold start emission control problem in a mid-size passenger car. The cold start controller is first designed in a single-input single-output (SISO) structure with three separate sliding surfaces, and then is redesigned based on a multiinput multi-output (MIMO) SMC design technique using nonlinear balanced realization.

Real-time control of Reactivity Controlled Compression Ignition (RCCI) during engine load and speed transient operation is challenging, since RCCI combustion phasing depends on nonlinear thermo-kinetic reactions that are controlled by dual-fuel reactivity gradients. This paper discusses the design and implementation of a real-time closed-loop combustion controller to maintain optimum combustion phasing during RCCI transient operations. New algorithms for real-time in-cylinder pressure analysis and combustion phasing calculations are developed and embedded on a Field Programmable Gate Array (FPGA) to compute RCCI combustion and performance metrics on cycle-by-cycle basis. This cycle-by-cycle data is then used as a feedback to the combustion controller, which is implemented on a real-time processor. A computationally efficient algorithm is introduced for detecting Start of Combustion (SOC) for the High Temperature Heat Release (HTHR) or main-stage heat release.

Increasing fuel injection pressure has enabled reduction of diesel emissions while retaining the advantage of the high thermal efficiency of diesel engines. With production diesel injectors operating in the range from 300 to 2400 bar, there is interest in injection pressures of 3000 bar and higher for further emissions reduction and fuel efficiency improvements. Fundamental understanding of diesel spray characteristics including very early injection and non-vaporizing spray penetration is essential to improve model development and facilitate the integration of advanced injection systems with elevated injection pressure into future diesel engines. Studies were conducted in an optically accessible constant volume combustion vessel under non-vaporizing conditions. Two advanced high pressure multi-hole injectors were used with different hole diameters, number of holes, and flow rates, with only one plume of each injector being imaged to enable high frame rate imaging.

A new press/die system for restraining force control has been developed in order to facilitate an increased level of process control in sheet metal forming. The press features a built-in system for controlling drawbead penetration in real time. The die has local force transducers built into the draw radius of the lower tooling. These sensors are designed to give process information useful for the drawbead control. This paper focuses on developing models of the drawbead actuators and the die shoulder sensors. The actuator model is useful for developing optimal control methods. The sensor characterization is necessary in order to develop a relationship between the raw sensor outputs and a definitive process characteristic such as drawbead restraining force (DBRF). Closed loop control of local specific punch force is demonstrated using the die shoulder sensor and a PID controller developed off-line with the actuator model.

This paper presents a response to the question: Simulation - mathematical manipulation or useful design tool? A mathematical model of a modulating valve in a transmission control system was developed to predict clutch pressure modulation characteristics. The transmission control system was previously reported in SAE Paper 850783 - “Electronic/Hydraulic Transmission Control System for Off-Highway Vehicles”. The comparison of simulation predictions with test data illustrates the effectiveness of simulation as a design tool. THE EVOLUTION OF COMPUTER hardware and simulation software has resulted in increased interest and usage of simulation for dynamic analysis of hydraulic systems. Most commercially available software is relatively easy to learn to use. The application of such software and the modeling techniques involved require a longer learning curve.