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The information needs of engines have increased dramatically over recent years. In order to achieve the levels of performance and endurance that are now required in the marketplace, engine operation increasingly employs sophisticated control with closed-loop operation of various functions. This control trend will continue as performance expectations increase, calibration times reduce and systems become more complex and dependent on a variety of sensors. Available and emerging technologies offer a range of solutions for sensor systems but success in any particular application is often difficult to analyze. This makes the prediction of future trends more difficult. This paper looks back at some recent developments and forward to the next few years. In addition to the sensors required, some consideration is also given to control systems, which have increased dramatically in sophistication.

Diesel engine control has already become complex, and in order to meet future emissions standards (such as Euro 4) it is likely to be the control system that will provide the needed performance increment. Common rail fuel injection offers yet more degrees of freedom which will need to be exploited as new emissions standards emerge. Whatever the emissions standards, there is a need to reduce risk at the earliest stages in the development of the powertrain. This will involve early and extensive simulation of the powertrain including its control system, sensors and actuators. What is the best way to achieve this using current tools? The result lies in a combination of a phenomenological model of the engine and a flexible controls environment. To illustrate the principles of developing prototype control systems, we will use the example of the CPower environment, which is a combination of a detailed engine simulation code (GT-Power) and the Simulink simulation environment.

Engineers need the most capable design support tools to reconcile the demands of the market, legislation, economic design and production. Simulation tools are a very effective support system. The optimization of the complete vehicle system for external noise radiation is very complex due to the interaction of the engine performance with the vehicle positioning. Simple predictive methods and assumptions are often not usefully accurate. The work described here covers an approach to combining rapid predictions of engine and vehicle performance with those of radiated noise from the various significant subsystems, to produce a useful, rapid, prediction tool for complete vehicle noise. A mono-dimensional gas flow code is used to provide a sufficiently accurate prediction of the engine power for vehicle performance prediction and also the noise output of intake and exhaust systems. Various approximate prediction methods are used to assemble an overall vehicle radiated noise prediction.

The successful application of noise source identification and reduction techniques, by timely and cost-effective integration of practical and analytical methods, can be demonstrated by case studies. The general areas under consideration include: Noise sources generated within the engine Noise radiation from the engine surfaces Vehicle interior and exterior noise

The way we look at organizations has changed. Requirements for consistent and high quality at affordable costs while meeting the competition from around the world, have meant that organizations are now more conscious of the need to use all their resources to the best effect. Over the past 20 years various management and organizational systems have come to be known as Quality Management Systems. This paper presents an overview of how the requirements of quality are reflected in organization structures, in both product and service orientated organizations. The basis of the paper is the International Standard series 9000, which has been adopted by many developed nations, coupled with some personal observations. This paper aims for a perspective which stresses the corporate needs for quality organization rather than a detailed prescription.

The effects of using different combustion systems on engine noise are reviewed including an examination of noise reduction methods such as shielding, enclosure and structural modifications. Comparisons are made of direct injection and indirect injection systems and a new noise prediction formula for IDI engines is proposed. The use of turbocharging is examined and the limiting effects of mechanical noise noted. The variation of exhaust emission levels with reduction of combustion noise is included.