Search Results

SAE J1939 is an emerging communications protocol for on-board electronics in agricultural and construction equipment as well as for heavy duty on-highway equipment. The standard supports ECUs with both statically and dynamically configured addresses. This paper examines the dynamic addressing process, the process for ECUs that select addresses during initial power-up. A state diagram is proposed to implement the process described in the standard. Simulation results of systems with up to 100 dynamically configured ECUs are presented. Use of a pseudo-random delay after a power-ON self test was successful in minimizing bus-off collisions and allowed initialization times of under 1 second for 30 ECU systems. Minimum bus-off states during initialization of 30 ECU networks occurred with pseudo-random delays having a range of 0 to 15 ms.

A virtual terminal (VT) is a network device that provides display and keyboard services to other devices on the netowork. A VT allows an operator to interact with other devices on a network. Before a screen can be displayed by the operator, the network device associated with the screen must secure memory within the terminal to store the screen. If there is not enough memory within the virtual terminal to store all screens, the memory must be managed dynamically. Much is known about memory management in the context of operating systems. In this study, traditional page replacement algorithms are considered for memory management within a virtual terminal. Algorithms are analyzed with respect to network load under various constraints. In addition, modifications to the existing algorithms are proposed. These modifications are considered to meet the unique demands required for in-vehicle networking.

Standardized Class C communication networks are being developed for use in construction and agricultural equipment. Both an ISO and SAE standards are being developed. This paper attempts to summarize both standards and to discuss potential application of the standards.

A review of artificial neural network (ANN) technique is presented. An application of a neural network in an embedded real-time feed-forward control system is described. Performance of the example system is quantified with respect to accuracy and execution time. The resulting 11 node network was converted to an embedded 8 bit micro-controller application and executed in 0.07 seconds per prediction.