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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).

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.

Lookup tables and functions are widely used in real-time embedded automotive applications to conserve scarce processor resources. To minimize the resource utilization, these lookup tables (LUTs) commonly use custom data structures. The lookup function code is optimized to process these custom data structures. The legacy routines for these lookup functions are very efficient and have been in production for many years. These lookup functions and the corresponding data structures are typically used for calibration tables. The third-party calibration tools are specifically tailored to support these custom data structures. These tools assist the calibrators in optimizing the control algorithm performance for the targeted environment for production. Application software typically contains a mix of both automatically generated software and manually developed code. Some of the same calibration tables may be used in both auto generated and hand-code [ 1 ] [ 2 ].

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.

Suitable and effective nutrient delivery systems will be required for both long-duration studies of plant growth and for implementation of bioregenerative life support technologies involving crop production in closed micro-gravity environments. Such environments are anticipated onboard a Space Station. The development of such systems hinges on acquiring the scientific and engineering knowledge necessary to design for micro-gravity operations. We have completed the preliminary design of a flight experiment called the Nutrient Delivery Testbed-1 (NDT-1) which will provide a substantial amount of information about the behavior of such systems in the space environment. The NDT-1 package includes a computer control subsystem, two motor-driven nutrient solution reservoirs, a nutrient solution composition monitoring subsystem, a solution sampling subsystem, three different nutrient delivery systems, and a plant surrogate.

The paper reviews the role of drawbeads in sheet metal stamping. The design of drawbeads is discussed in depth, with treatment of different bead cross sections, bead end shapes, and bead materials. International standards and practices are included. This is followed by the historical development of the modeling of the drawbead restraining force, starting with basic equilibrium approaches, and leading to the use of the finite element method which permits the study of drawbead effects on sheet metal flow in three dimensions. Finally, the potential of active drawbeads is described based upon ongoing research which is directed toward closed-loop computer control of the stamping process through adjustment of the drawbead penetration.

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.

The following paper discusses alternative strategies for reducing noise and emission production from a two-stroke snowmobile. Electric, two-stroke and four-stroke solutions were analyzed and considered for entry in the Clean Snowmobile Challenge (CSC) 2000. A two-stroke solution was utilized primarily due to time constraints. Complete snowmobile competition results are provided. The electric solution, while the most effective at reducing emissions, is negatively impacted by weight and cost. A modified two-stroke solution, limited by cost and complexity, does not provide the required improvements in emissions. A four-stroke solution reduces noise and emissions and provides an acceptable trade-off between noise, emissions, performance and cost.

The drive of Design for the Environment is to reduce the environmental impact of both design and manufacturing processes. The most frequent method recommended is to substitute better materials and processes. However, there are processes that will continue to have undesirable environmental impacts due to the lack of knowledge of better methods. These processes are critical to manufacturing of products and can not be eliminated. All possible substitutions appear to have worse impacts. This paper explores modeling these processes and imposing a control method which permits an improvement of the environmental impact.

The Electronic Control Unit (ECU) of an Electric Power Steering (EPS) system is a core device to decide how much assistance an electric motor applies on a steering wheel. The EPS ECU plays an important role in EPS systems. The effectiveness of an ECU needs to be thoroughly tested before mass production. Hardware-in-the-loop simulation provides an efficient way for the development and testing of embedded controllers. This paper focuses on the development of a HiL system for testing EPS controllers. The hardware of the HiL system employs a dSPACE HiL simulator. The EPS plant model is an integrated model consisting of a Vehicle Dynamics model of the dSPACE Automotive Simulation Model (ASM) and the Nexteer Steering model. The paper presents the design of an EPS HiL system, the simulation of sensors and actuators, the functions of the ASM Vehicle Dynamics model, and the integration method of the ASM Vehicle Dynamics model with a Steering model.

The proliferation of small silicon micro-chips has led to a large assortment of low-cost transducers for data acquisition. Production vehicles on average exploit more than 60 on board sensors, and that number is projected to increase beyond 200 per vehicle by 2020. Such a large increase in sensors is leading the fourth industrial revolution of connectivity and autonomy. One major downfall to installing many sensors is compromises in their accuracy and processing power due to cost limitations for high volume production. The same common errors in data acquisition such as sampling, quantization, and multiplexing on the CAN bus must be accounted for when utilizing an entire array of vehicle sensors. A huge advantage of onboard sensors is the ability to calculate vehicle parameters during a daily drive cycle to update ECU calibration factors in real time. One such parameter is driveline damping, which changes with gear state and drive mode. A damping value is desired for every gear state.