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Autonomous vehicle operation is dependent upon accurate position estimation and thus a major concern of implementing the autonomous navigation is obtaining robust and accurate data from sensors. This is especially true, in case of Inertial Measurement Unit (IMU) sensor data. The IMU consists of a 3-axis gyro, 3-axis accelerometer, and 3-axis magnetometer. The IMU provides vehicle orientation in 3D space in terms of yaw, roll and pitch. Out of which, yaw is a major parameter to control the ground vehicle’s lateral position during navigation. The accelerometer is responsible for attitude (roll-pitch) estimates and magnetometer is responsible for yaw estimates. However, the magnetometer is prone to environmental magnetic disturbances which induce errors in the measurement.

As both the number and complexity of electronic control system applications on earthmoving equipment and on-highway trucks increase, so does the effort associated with developing and maintaining control strategies implemented in embedded systems. A new tool was recently introduced by Sigma Technology of Ann Arbor, Michigan, that provides the capability to perform rapid prototyping of production embedded systems. The rapid prototyping process includes system modeling, control algorithm synthesis, simulation analysis, source code generation and vehicle implementation. The results of incorporating this tool in the control system design process include improved control performance, improved system reliability/robustness, and significantly reduced development/maintenance costs.

This paper identifies potential performance benefits and computational costs of applying advanced multivariable control theory concepts to coordinate the control of a general multi-degree-of-freedom fuel system. The control variables are injection duration and pressure. The focus is on the design of a robust multi-input multi-output controller using H-infinity and mu synthesis methodology to coordinate the control of injection duration and pressure; reduce overshoots and system sensitivity to parameter variations caused by component aging. Model reduction techniques are used to reduce the order of the H-infinity controller to make it practically implementable. Computer simulation is used to test the robust performance of a generic engine and fuel system model controlled by the reduced order H-infinity controller and a traditional proportional plus integral controller.

Ducted fuel injection (DFI) was tested for the first time in a heavy-duty diesel metal engine. It was implemented on a Caterpillar 2.5-liter single-cylinder heavy-duty diesel engine fitted with a common rail fuel system and a Tier 4 final production piston. Engine tests consisted of single-injection timing sweeps at A100 and C100, where rail pressure and exhaust gas recirculation (EGR) were also varied. A 6-hole fuel injector tip with 205 am orifices was used with a 130° spray angle and rail pressures up to 250 MPa. The ducts were 14 mm long, had a 2.5 mm inner diameter, and were placed 3.8 mm away from the orifice exits. The ducts were attached to a base, which in turn was attached to the cylinder head with bolts. Furthermore, alignment of the ducts and their corresponding fuel jets was accomplished.

All around the world, steps are being taken to improve the quality of our environment. Prominent among these are the definition, implementation, and attainment of increasingly stringent emissions regulations for all types of engines, including off-highway diesels. These rigorous regulations have driven use of technologies like after-treatment, advanced air systems, and advanced fuel systems. Fuel dispensed off-highway is routinely and significantly dirtier than fuel from on-highway outlets. Furthermore, fuels used in developing countries can be up to 30 times dirtier than the average fuels in North America. Poor fuel cleanliness, coupled with the higher pressures and performance demands of modern fuel systems, create life challenges greater than encountered with cleaner fuels. This can result in costly disruption of operations, loss of productivity, and customer dissatisfaction in the off-highway market.