In modern production diesel engine control systems, fuel path control is still largely conducted through a system of tables that set mode, timing and injection quantity and with common rail systems, rail pressure. In the hands of an experienced team, such systems have proved so far able to meet emissions standards, but they lack the analytical underpinning that lead to systematic solutions.
In high degree of freedom systems typified by modern fuel injection, there is substantial scope to deploy optimising closed loop strategies during calibration and potentially in the delivered product. In an optimising controller, a digital algorithm will explicitly trade-off conflicting objectives and follow trajectories during transients that continue to meet a defined set of criteria.
Such an optimising controller must be based on a model of the system behaviour which is used in real time to investigate the consequences of proposed control actions. Models are critical to success, during design and operation of the control system.
The formulation of model structure required in the investigation of fuel path has two aspects: linear models to be used in multi-model control schemes, and nonlinear models required to support the control design process. Experimental conditions are designed to collect data for model fitting and to collect data for validation. Special purpose engine controls were designed and implemented in order to support data collection and with a view to testing the resulting control systems. The results demonstrate that the modeling of fuel path is feasible to support both control design and the real time operation of the closed loop control of the fuel path devices.