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"Smart'' sensor concepts must be considered as the demands of advanced automotive systems increase. These concepts are strongly influenced by the architectural and dependability aspects of future systems. Key features of smart sensors are: communication (two way) with a digital data bus, self- calibration, error source compensation, self-diagnostics, and programmability for "plug and play.'' This paper contains a discussion of the basic future sensor requirements, and it assesses four major sensor technologies with respect to their suitability to meet these requirements. For each technology, the merits and demerits will be reviewed and an example sensing application will be given in order to demonstrate how the technology can be adapted to meet the future requirements.

A single-crystal silicon capacitive acceleration sensor for low-g applications has been developed. The sensor element itself is formed entirely from single crystal silicon, giving it exceptional stability over time and temperature and excellent shock resistance. The sensor is produced using low-cost, high volume processing, test and calibration. The sensor integrated circuit (IC) contains a proofmass which moves in response to applied accelerations. The position of the proofmass is capacitively detected and processed by an interface IC. The sensor/interface IC system is packaged in a small outline IC (SOIC) package for printed circuit board mounting. The module is designed to measure full scale accelerations in the 0.75g to 3g range to suit a variety of automotive, industrial and consumer applications

Intense competition in the automotive industry requires continuous reduction in innovation cycle time, even as corporations are downsizing and system complexity is increasing. Subsequently, the application of recently introduced Rapid Algorithm Development (RAD) tools has facilitated significant advances in the development of embedded control systems. The RAD steps include system modeling, control algorithm design, simulation analysis, automated calibration design, and vehicle implementation through automatic code generation. The application of RAD tools and the associated benefits are described, specifically in the context of Engine Management Systems (EMS). Such benefits include significant reductions in development cycle time, open architecture, automated calibration, and information reuse.

This paper presents a theoretical and experimental study of a cylinder deactivation valvetrain system for the integration into an Engine Management System (EMS). A control-oriented lumped parameter model of the deactivation valvetrain system is developed and implemented using Matlab/Simulink, and validated by experimental data. Through simulation and experimental data analysis, the effect of operating conditions on the dynamic response is captured and characterized, over a wide range of operating conditions. The algorithm provides a basis for the calibration of the deactivation hardware. The generic characterization of the dynamic response can simplify the calibration parameters for the implementation in engine management systems.

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.

This paper presents a brake pressure estimation algorithm for Delphi Traction Control Systems (TCS). A control oriented lumped parameter model of a brake control system is developed using Matlab/Simulink. The model is derived based on a typical brake system and is generic to other types of brake control hardware systems. For application purposes, the model is simplified to capture the dominant dynamic brake pressure response. Vehicle experimental data collected under various scenarios are used to validate the algorithm. Simulation results show that the algorithm gives accurate pressure estimation. In addition, the calibration procedure is greatly simplified