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For a series plug-in hybrid electric vehicle (PHEV), it is critical that batteries be sized to maximize vehicle performance variables, such as fuel efficiency, gasoline savings, and zero emission capability. The wide range of design choices and the cost of prototype vehicles calls for a development process to quickly and systematically determine the design characteristics of the battery pack, including its size, and vehicle-level control parameters that maximize the net present value (NPV) of a vehicle during the planning stage. Argonne National Laboratory has developed Autonomie, a modeling and simulation framework. With support from The MathWorks, Argonne has integrated an optimization algorithm and parallel computing tools to enable the aforementioned development process. This paper presents a study that utilized the development process, where the NPV is the present value of all the future expenses and savings associated with the vehicle.

In response to marketplace demand for increased engine performance and economy, spark-ignition (SI) engine applications with dual-independent variable cam-phaser actuators (DIVCP) are now commonplace. In this paper, the minimum number of test measurements required to optimally calibrate the steady-state spark advance and cam-phaser settings of a SI DIVCP engine was determined, using a high-fidelity model of a 2.2L SI DIVCP engine with predictive combustion capability as a basis. A calibration development process was designed to objectively determine the minimum number of torque vs. spark advance sweeps required for the SI DIVCP engine. First, Torque production results from calibration tables based on cost-feasible sets of 52, 96, 173, 250, 329, and 406 sweeps were determined. Next, calibration reference tables were developed from an exhaustive data collection process based on 10,000 sweeps.

To improve vehicle driveability in diesel powertrain applications, it is desirable to coordinate engine and transmission control functions. Transmission control algorithms in diesel powertrains can use torque information from the engine controller under a wide variety of powertrain operating conditions to improve shift quality. Unfortunately, direct engine torque measurement using powertrain sensors in production hardware is considered expensive. The aim of the work in this paper was to evaluate the feasibility of using an embedded torque estimation algorithm as an alternative to new sensor hardware in an off-road diesel application. The feasibility of estimating torque in a conventional engine control unit (ECU) was proven by developing and evaluating an engine torque estimator on an MPC555 processor using model-based design approaches.

A wide-range Air-Fuel Ratio sensor (WRAF) response diagnostic algorithm was developed for production application in Gasoline Direct Injection (Gas-DI) powertrains to fulfill On Board Diagnostic (OBD) legislative requirements [1] for wide-range oxygen sensors. The algorithm measures the response of a wide-range air-fuel ratio (AFR) sensor signal to an input AFR signal of known amplitude to determine whether degradation in sensor responsiveness is severe enough to cause a failure of legal emissions requirements. A practical IIR (Infinite Impulse Response) digital bandpass filter design was used in series with a rectifier and low-pass filter to process the AFR sensor signal for comparison to a reference signal amplitude. The IIR filter was designed with a moveable pass-band to enable the algorithm to be used at variable frequencies during intrusive and non-intrusive sensor diagnostic tests.

A Wide-Range Air-Fuel-Ratio (AFR) control algorithm was developed for production application in Direct Injection Gasoline (DI-G) powertrains. The algorithm controls AFR to a scheduled target by modifying open-loop fuel injection timing duration using a Wide-Range AFR sensor measurement for feedback. A physically based hybrid State Estimator design was used to account for event-based engine delays and time-based sensor measurement characteristics to determine the error between target and measured AFR. The State Estimator was designed to minimize algorithm size, calibration burden, and engine controller throughput demand. A time based, gain-scheduled Proportional-Integral control algorithm design was used to correct AFR errors. Non-physical estimation and control functions were designed for application with time-based updates to minimize engine controller throughput demand.

A Barometric Pressure Estimator (BPE) algorithm was implemented in a production speed-density Engine Management System (EMS). The BPE is a model-based, easily calibrated algorithm for estimating barometric pressure using a standard set of production sensors, thereby avoiding the need for a barometric pressure sensor. An accurate barometric pressure value is necessary for a variety of engine control functions. By starting with the physics describing the flow through the induction system, an algorithm was developed which is simple to understand and implement. When used in conjunction with the Pneumatic and Thermal State Estimator (PSE and TSE) algorithms [2], the BPE requires only a single additional calibration table, generated with an automated processing routine, directly from measured engine data collected at an arbitrary elevation, in-vehicle or on a dynamometer. The algorithm has been implemented on several different engines.

An event-based transient fuel compensator (TFC) algorithm was developed for production application on SPFI gasoline engines. The independent parameters of the TFC were related to fundamental mass-transfer principles from the research of Gilliland and Sherwood [1] to simplify cold-driveability and emissions calibration activities. A compact intake valve temperature model was developed to further simplify calibration. Digital Control Theory was applied to the calibration structure of the algorithm to clarify the relationship between compensator stability and parameter settings. In its final production algorithm form on a 2.4L DOHC engine application, the TFC met the required subjective cold-driveability requirements and emission standards with a significant reduction in transient fuel calibration complexity.