Adaptive Engine Control Using GPS-Based Parasitic Load Prediction

The system performs preliminary action by predicting future parasitic loads using GPS location and geographic information before initiating regeneration events. The controller forecasts upcoming engine loads based on terrain data, route information, and historical patterns, then schedules regeneration events to occur during periods of predicted low load. This advance planning allows coordination of multiple parasitic loads (regeneration, air conditioning, radio) to prevent simultaneous occurrence, thereby maintaining engine performance while ensuring after-treatment system reliability.

The system changes the timing parameter of regeneration events based on predicted driving conditions and geographic information. By analyzing future route data including elevation changes, traffic patterns, and terrain, the controller selects optimal moments when engine load is naturally lower, allowing temperature raising events to occur with minimal impact on overall fuel consumption. This dynamic parameter adjustment ensures effective soot removal while minimizing the energy penalty associated with artificial temperature increases.

The controller performs preliminary scheduling of multiple parasitic loads by forecasting future engine power requirements using geographic information and GPS data. It identifies time windows where predicted engine load is low, then coordinates the timing of regeneration events, air conditioning operation, and radio power consumption to occur within these windows. This prevents simultaneous operation of multiple parasitic loads that would otherwise cause excessive power demand, maintaining engine power output while ensuring regeneration completion.