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Impact of driving patterns on fuel economy is significant in hybrid electric vehicles (HEVs). Driving patterns affect propulsion and braking power requirement of vehicles, and they play an essential role in HEV design and control optimization. Driving pattern conscious adaptive strategy can lead to further fuel economy improvement under real-world driving. This paper proposes a real-time driving pattern recognition algorithm for supervisory control under real-world conditions. The proposed algorithm uses reference real-world driving patterns parameterized from a set of representative driving cycles. The reference cycle set consists of five synthetic representative cycles following the real-world driving distance distribution in the US Midwestern region. Then, statistical approaches are used to develop pattern recognition algorithm. Driving patterns are characterized with four parameters evaluated from the driving cycle velocity profiles.

Greenhouse gas (GHG) emission targets are becoming more stringent for both automakers and electricity generators. With the introduction of plug-in hybrid and electric vehicles, transportation and electricity generation sectors become connected. This provides an opportunity for both sectors to work together to achieve the cost efficient reduction of CO2 emission. In addition, the abundant natural gas (NG) in USA is drawing increased attention from both policy makers and various industries due to its low cost and low carbon content. NG has the potential to ease the pressure from CO2 emission constraints for both the light duty vehicle (LDV) and the electricity generation sectors while simultaneously reducing their fuel costs. To quantify the benefit of this collaboration, an analytical model is developed to evaluate the total societal cost and CO2 emission for both sectors.

Over half of the greenhouse gas (GHG) emissions in the United States come from the transportation and electricity generation sectors. To analyze the potential impact of cross-sector cooperation in reducing these emissions, we formulate a bi-level optimization model where the transportation sector can purchase renewable energy certificates (REC) from the electricity generation sector. These RECs are used to offset emissions from transportation in lieu of deploying high-cost fuel efficient technologies. The electricity generation sector creates RECs by producing additional energy from renewable sources. This additional renewable capacity is financed by the transportation sector and it does not impose additional cost on the electricity generation sector. Our results show that such a REC purchasing regime significantly reduces the cost to society of reducing GHG emissions. Additionally, our results indicate that a REC purchasing policy can create electricity beyond actual demand.

Designing a control system that can robustly detect faulted emission control devices under all environmental and driving conditions is a challenging task for OEMs. In order to gain confidence in the control strategy and the values of tunable parameters, the test vehicles need to be subjected to their limits during the development process. Complexity of modern powertrain systems along with the On-Board Diagnostic (OBD) monitors with multidimensional thresholds make it difficult to anticipate all the possible scenarios. Finding optimal solutions to these problems using traditional calibration processes can be time and resource intensive. A possible solution is to take a data driven calibration approach. In this method, a large amount of data is collected by collaboration of different groups working on the same powertrain. Later, the data is mined to find the optimum values of tunable parameters for the respective vehicle functions.

Automotive manufacturers continue to move further toward powertrain electrification. There are already many hybrid electric vehicles on the market that are based on a variety of system architectures. Ford Motor Company has investigated a new Dual Drive configuration that promises to overcome some of the attribute deficiencies associated with current architectures. The primary objective of this development project was to demonstrate the fuel economy potential of this system in a vehicle. To accomplish this objective, the team used an internally developed, formal Controls Development Process (CDP) for the control system design and validation. This paper describes the development of the vehicle control system in the context of this process.

Only a part of the energy released from the fuel during combustion is converted to useful work in an engine. The remaining energy is wasted and the exhaust stream is a dominant source of the overall wasted energy. There is renewed interest in the conversion of this energy to increase the fuel efficiency of vehicles. There are several ways this can be accomplished. This work involves the utilization thermoelectric (TE) materials which have the capability to convert heat directly into electricity. A model was developed to study the feasibility of the concept. A Design of Experiment was performed to improve the design on the basis of higher power generation and less TE mass, backpressure, and response time. Results suggest that it is possible to construct a realistic device that can convert part of the wasted exhaust energy into electricity thereby improving the fuel economy of a gas-electric hybrid vehicle.

A belt driven Front End Accessory Drive (FEAD) is used to efficiently supply power to accessory components on automotive engines. The total energy absorbed by the FEAD consists of the accessory component requirements, the belt deformation and friction losses as well as the bearing losses. The accessory component torque requirements provide accessory function such as air conditioning, fluid pumping and electrical power generation. Alternatively, belt related torque losses are a significant parasitic loss, since they do not contribute any useful work. This paper will explain the source of energy loss in FEADs and outline a comprehensive strategy to reduce it. Test results comparing the effect of reduced friction on fuel consumption will be presented as well.

An advanced powertrain cooling system with appropriate control strategy and active actuators allows greater flexibility in managing engine temperatures and operating near constraints. An organized controls development process is necessary to allow comparison of multiple configurations to select the best way forward. In this work, we formulate, calibrate and validate a Model Predictive Controller (MPC) for temperature regulation and constraint handling in an advanced cooling system. A model-based development process was followed; where the system model was used to develop and calibrate a gain scheduled linear MPC. The implementation of MPC for continuous systems and the modification related to implementing switching systems has been described. Multiple hardware configurations were compared with their corresponding control system in simulations. The system level requirements were translated into MPC calibration parameters for consistent comparison between multiple configurations.

Automotive Product Development organisations are challenged with ever increasing levels of systems complexity driven by the introduction of new technologies to address environmental concerns and enhance customer satisfaction within a highly competitive and cost conscious market. The technical difficulty associated with the engineering of complex automotive systems is compounded by the increase in sophistication of the control systems needed to manage the integration of technology packages. Most automotive systems have an electro-mechanical structure with control and software features embedded within the system. The conventional methods for design analysis and synthesis are engineering discipline focused (mechanical, electrical, electronic, control, software).

Ford Motor Company has developed a full hybrid electric vehicle with a power-split hybrid powertrain. There are constraints imposed by the high voltage system in such an HEV, that do not exist in conventional vehicles. A significant controls problem that was addressed in the Ford Escape and Mercury Mariner Hybrids was the determination of the desired powertrain operating point such that the vehicle attributes of fuel economy, performance and drivability are met, while satisfying these new constraints. This paper describes the control system that addressed this problem and the tests that were designed to verify its operation.

A four valve controller and electronic control circuits were developed to control the displacement of hydrostatic pump/motors (P/M's) utilized in an automobile with a hydrostatic transmission and hydropneumatic accumulator energy storage. Performance of the control system was evaluated. The controller uses four high-speed, two-way, single-stage poppet valves, functioning in the same manner as a 4-way, 3-position spool valve. Two such systems were used to control the displacement of two P/Ms, each system driving a front wheel of the vehicle. The valves were controlled electronically by a distributed-control dead-band circuit and valve driver boards. Testing showed that the control system's time response satisified driving demand needs, but that the control system's error was slightly larger than desired. This may lead to complications in some of the vehicle's operating modes.

In automotive industry, the interior quietness is a task that manufacturers are constantly improving for passenger comfort. In order to improve the interior quietness there are considered the contribution of structure borne and airborne noise. An alternator used in vehicles for generation of electricity can be considered as a contributor of airborne noise. Due to the characteristics of an alternator, it could radiate mechanical, aerodynamic and electromagnetic noise. The last two characteristics are normally perceived by customer during powertrain and idle evaluation. In this paper is presented correlation between interior noise measured on road test and alternator radiated noise measured on bench test.

While SAE double inverted flares have been in use for decades, leaking joints continue to be a problem for OEMs in production settings consuming time and energy to detect and correct them before releasing vehicles from the assembly plant. It should be noted that this issue is limited to first-time vehicle assembly; once a flared brake tube joint is sealed at the assembly plant it remains sealed during normal customer usage. From their inception through the late 1980s most brake tubes have been 3/16″ nominal diameter. With the advent of higher flow requirements of Traction Control and Yaw/Stability control systems, larger tubes of 1/4″ and 5/16″ size have also been introduced. While it was known that the first-time sealing capability of the 3/16″ joint was not 100%, leakers were generally containable in the production environment and the joint was regarded as robust.

The desire for improved vehicle fuel economy, driven by high gas prices and concerns over energy independence, have sparked interest and demand for hybrid electric vehicles. Hybrid electric vehicle propulsion systems exhibit complex interactions which need to be understood in order to maximize fuel economy over the range of operating modes. Model-based development processes which use vehicle system models capable of representing the functional behaviors with embedded controls are needed for fast, efficient design of vehicle control systems which manage overall energy usage. Model-based vehicle system development processes have been employed for a Dual Drive HEV system. The process for creating these vehicle system models is described along with an approach for using these models to develop HEV systems. Details of key subsystem models and the process for integration of full vehicle implementation level controls are discussed.

In future vehicles (e.g. fuel cell vehicles, hybrid electric vehicles), the electrical system will have an important impact on the mechanical systems in the car (e.g. powertrain, steering). Furthermore, this coupling will become increasingly important over time. In order to develop effective designs and appropriate control systems for these systems, it is important that the plant models capture the detailed physical behavior in the system. This paper will describe models of two electrical components, a battery and a supercapacitor, which have been modeled in two ways: (i) modeling the plant and controller using block diagrams in Simulink and (ii) modeling the plant and controller in Dymola followed by compiling this model to an S-function for simulation in Simulink. Both the battery and supercapacitor model are based on impedance spectroscopy measurements and can be used for highly dynamic simulations.

A hybrid electric vehicle requires a complex control system to effectively manage vehicle level attributes while maximizing fuel efficiency. The control system interactions necessitate a hierarchical control structure in which one controller, the vehicle system controller, directs the functions of the lower level controllers. This paper outlines a model-based method that allows a controls team to design and validate a vehicle system controller for use in a hybrid electric vehicle.

The new 2005 Brazilian emissions legislation for diesel vehicles, based on EURO III, requires more complex emission control systems, like electronic engine management systems. The introduction of an electronic engine management system allows improvement in important aspects to the customer perception, such as drivability and vehicle noise levels. The objective of this paper is to compare the gains in terms of drivability of vehicles with electronic engine management system and conventional mechanical system, based on acceleration curves, driving behavior and vehicle speed

Models often use time rather than strokes (crank-angle) as the independent variable to describe engine dynamics despite the fact that the dynamics of an internal combustion engine are intrinsically linked to the combustion events. In this paper, two models are developed in parallel in which not only the independent variable is changed but the notion of mass flows as well: flows are in [g/s] for the time-based model and in [g/st] for the event-based model. Both models are of the same computational complexity and show the same accuracy in validation. The investigation of the model properties shows that variations in the flow-related parameters are reduced by a factor of two to five for the event-based model. However, those of the crankshaft dynamics are increased. It is concluded that the model should be chosen in context of the control system to be designed.

We propose a steering controller for automated trailer backup, which can be used on tractor-trailer configurations including fifth wheel campers and gooseneck style trailers. The controller steers the trailer based on real-time driver issued trailer curvature commands. We give a stability proof for the hierarchical control system, and demonstrate robustness under a specific set of modeling errors. Simulation results are provided along with experimental data from a full-size pickup truck and 5th wheel trailer.

The development of an automatic control system for a towing dynamometer used for testing is described in this paper. The process involved the deployment of new power electronics circuit boards, a TELMA retarder, instrumentation and a human machine interface (HMI) achieved through an open source platform. The purpose of this platform is to have a low cost system that allows further function development, data acquisition and communication with other devices. This system is intended as a novel solution that will allow closed loop and automated tests integrated with PCM data for engine calibration. It is projected to be part of a flexible calibration system with direct communication to the interfaces used during development (ATI, ETAS), which will be used to achieve lean test and development schedules.