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This paper presents an overview of the connected controls and optimization system for vehicle dynamics and powertrain operation on a light-duty plug-in multi-mode hybrid electric vehicle developed as part of the DOE ARPA-E NEXTCAR program by Michigan Technological University in partnership with General Motors Co. The objective is to enable a 20% reduction in overall energy consumption and a 6% increase in electric vehicle range of a plug-in hybrid electric vehicle through the utilization of connected and automated vehicle technologies. Technologies developed to achieve this goal were developed in two categories, the vehicle control level and the powertrain control level. Tools at the vehicle control level include Eco Routing, Speed Harmonization, Eco Approach and Departure and in-situ vehicle parameter characterization.

A high-fidelity multi-step global kinetic Selective Catalytic Reduction (SCR) model which can predict SCR performance in engine exhaust systems is desirable for optimizing the SCR system, designing on-vehicle control systems and on-board diagnostic (OBD) functions. In this study, a Cu-zeolite SCR catalyst in the exhaust of a 2010 Cummins 6.7L ISB diesel engine was experimentally studied under both steady-state and transient conditions. Steady-state engine tests spanned SCR inlet temperatures from 250 to 400°C with a constant space velocity of 60 khr-1. A 1-D Cu-zeolite model originally developed from reactor data was improved and calibrated to the steady-state engine experimental data. The calibrated model is capable of predicting NO/NO₂ reduction, NH₃ slip, and NH₃ storage associated phenomena.

Automotive exhaust emissions of polynuclear aromatic (C16+) hydrocarbons (PNA) were reduced by 65-70% by current emissions control systems and by about 99% by two experimental advanced emission control systems. At a given level of emission control, PNA emission was primarily controlled by fuel PNA content through the transient storage of PNA in engine deposits and their later emission under more severe engine operating conditions. A relatively minor contribution to PNA emission was made by PNA synthesized from lower molecular weight fuel aromatics, particularly C10-C14 aromatics. Deposit-related PNA emissions were linearly correlated with the PNA content of the deposit formation fuel. In comparison with a fuel of field-average PNA content (0.5 ppm benzo(a)pyrene), a field-maximum fuel (3 ppm) contained 4 to 7 times as much of three major PNA species and caused 3 to 5 times higher emissions of these species.

A microprocessor controlled lubricating oil cooling system of truck diesel engine was designed to minimize the sump oil temperature fluctuation during start-up and nonsteady engine operations. Model reference adaptive control method is utilized in the control system design. The analysis involved in the design of the microprocessor controlled oil cooling system, and the applications of a special vehicle-engine-cooling system (VEC) computer simulation code in the implementation and testing of the model reference adaptive control strategy are described. Using the VEC simulation code, the performance of the microprocessor controlled oil cooling system and the conventionally controlled oil cooling systems were compared for the ATB, temperature disturbances, and cold weather transient tests. An explanation of each test, as well as a review of the results of comparison tests are presented.

A thermal management system for heavy duty diesel engines is presented for maintaining acceptable and constant engine temperatures over a wide range of operational conditions. It consists of a computer controlled variable speed coolant pump, a position controlled thermostat, and a model-based control strategy. An experimentally validated, diesel engine cooling system simulation was used to demonstrate the thermal management system's capability to reduce power consumption. The controller was evaluated using a variety of operating scenarios across a wide range of loads, vehicle speeds, and ambient temperatures. Three metrics were used to assess the effects of the computer controlled system: engine temperature, energy savings, and cab temperature. The proposed control system provided very good control over the engine coolant temperatures while maintaining engine metal temperatures within a desired range.

An adaptive control system which determines the optimum system parameters based on the engine response to changes in those parameters, has been tested as an ignition timing control system on several gaseous fueled engines. The changes in the MBT timing for speed, load, air-fuel ratio, and fuel type were explored. The ability of the control system to correct the timing for these parameters was demonstrated. An air-fuel ratio control based on the same technique is also discussed.

In this paper, a model-based linear estimator and a non-linear control law for an Fe-zeolite urea-selective catalytic reduction (SCR) catalyst for heavy duty diesel engine applications is presented. The novel aspect of this work is that the relevant species, NO, NO2 and NH3 are estimated and controlled independently. The ability to target NH3 slip is important not only to minimize urea consumption, but also to reduce this unregulated emission. Being able to discriminate between NO and NO2 is important for two reasons. First, recent Fe-zeolite catalyst studies suggest that NOx reduction is highly favored by the NO 2 based reactions. Second, NO2 is more toxic than NO to both the environment and human health. The estimator and control law are based on a 4-state model of the urea-SCR plant. A linearized version of the model is used for state estimation while the full nonlinear model is used for control design.

Four-way, integrated, diesel emission control systems that combine selective catalytic reduction for NOx control with a continuously regenerating trap to remove diesel particulate matter were evaluated under real-world, on-road conditions. Tests were conducted using a semi-tractor with an emissions year 2000, 6-cylinder, 12 L, Volvo engine rated at 287 kW at 1800 rpm and 1964 N-m. The emission control system was certified for retrofit application on-highway trucks, model years 1994 through 2002, with 4-stroke, 186-373 kW (250-500 hp) heavy-duty diesel engines without exhaust gas recirculation. The evaluations were unique because the mobile laboratory platform enabled evaluation under real-world exhaust plume dilution conditions as opposed to laboratory dilution conditions. Real-time plume measurements for NOx, particle number concentration and size distribution were made and emission control performance was evaluated on-road.

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.

The hardware and software for a prototype computer controlled cooling system for a diesel powered truck has been designed and tested. The basic requirements for this system have been defined and the control functions, previously investigated in a study using the computer simulation model, were incorporated into the software. Engine dynamometer tests on the MACK-676 engine, comparing the conventional cooling system and the computer controlled system, showed the following advantages of the computer controlled system: 1. The temperature level to which the engine warms up to at low ambient temperature, was increased. 2. The faster shutter response reduced the temperature peaks and decreased total fan activity time. 3. The faster fan response reduces fan engagement time which should improve truck fuel economy.