Search Results

The importance of including turbocharger dynamics in diesel engine models are studied, especially when optimization techniques are to be used to derive the optimal controls. This is done for two applications of diesel engines where in the first application, a diesel engine in wheel loader powertrain interacts with other subsystems to perform a loading operation and engine speed is dictated by the wheel speed, while in the second application, the engine operates in a diesel-electric powertrain as a separate system and the engine speed remains a free variable. In both applications, mean value engine models of different complexities are used while the rest of system components are modeled with the aim of control study. Optimal control problems are formulated, solved, and results are analyzed for various engine loading scenarios in the two applications with and without turbocharger dynamics.

The combustion process has a high impact on the engine efficiency, and in the search for efficient engines it is of interest to study the combustion. Optimization and optimal control theory is used to compute the most efficient combustion profiles for single zone model with heat transfer and crevice effects. A model is first developed and tuned to experimental data, the model is a modification of the well known Gatowski et al.-model [1]. This model is selected since it gives a very good description of the in-cylinder pressure, and thus the produced work, and achieves this with a low computational complexity. This enables an efficient search method that can maximize the work to be developed. First, smooth combustion profiles are studied where the combustion is modeled using the Vibe function, and parametric optimization is used to search for the optimal profile.

The work extends a methodology, for searching for optimal heat release profiles, by adding complex constraints on states. To find the optimum heat release profile a methodology, that uses available theory and methods, was developed that enables the use of state of the art optimal control software to find the optimum combustion trace for a model. The methodology is here extended to include constraints and the method is then applied to study how sensitive the solution is to different effects such as heat transfer, crevice flow, maximum rate of pressure rise, maximum pressure, knock and NO generation. The Gatowski single zone model is extended to a pseudo two zone model, to get an unburned zone that is used to describe the knocking and a burned zone for NO generation. A modification of the extended Zeldovich mechanism that makes it continuously differentiable, is used for NO generation.

Downsizing and turbocharging is a proven technology for fuel consumption reduction in vehicles. To further improve the performance, electrified components in the turbocharger arrangements have been proposed, and investigations have shown acceleration improvements, emission reductions, and further fuel conversion efficiency benefits. Simulation tools play an important role in the design process as the interplay between component selection, control strategy, system properties and constraints is very complex. Evaluations are performed with respect to BSFC map, fuel consumption in a drive cycle, acceleration performance, as well as many other aspects. A component-based engine and vehicle model is developed and evaluated to facilitate the process of assessing and optimizing the performance of e.g. engine, charging system, and electrical machine components. Considerations of the execution time and model fidelity have resulted in a choice of models in the mean value engine model family.

Today’s need for fuel efficient vehicles, together with increasing engine component complexity, makes optimal control a valuable tool in the process of finding the most fuel efficient control strategies. To efficiently calculate the solution to optimal control problems a gradient based optimization technique is desirable, making continuously differentiable models preferable. Many existing control-oriented Diesel engine models do not fully posses this property, often due to signal saturations or discrete conditions. This paper offers a continuously differentiable, mean value engine model, of a heavy-duty diesel engine equipped with VGT and EGR, suitable for optimal control purposes. The model is developed from an existing, validated, engine model, but adapted to be continuously differentiable and therefore tailored for usage in an optimal control environment. The changes due to the conversion are quantified and presented.

To investigate the optimal controls of a diesel-electric powertrain during a torque controlled gearshift, a powertrain model is developed. A validated diesel-electric model is used as the power source and the transmission dynamics are described by different sets of differential equations during torque phase, synchronization phase and inertia phase of the gearshift. Using the developed model, multi-phase optimal control problems are formulated and solved. The trade-off between gearshift duration and driveline oscillations are calculated and efficient gearshift transients for a diesel-electric and pure diesel powertrain are then compared and analyzed.

Variable compression engines are a mean to meet the demand on lower fuel consumptions. A high compression ratio results in high engine efficiency, but also increases the knock tendency. On conventional engines with fixed compression ratio, knock is avoided by retarding the ignition angle. The variable compression engine offers an extra dimension in knock control, since both ignition angle and compression ratio can be adjusted. A vital question is thus what combination of compression ratio and ignition angle should be used to achieve maximum engine efficiency. Fuel optimal control of a variable compression engine is studied and it is shown that a crucial component is the model for the engine torque. A model for the produced work that captures the important effects of ignition and compression ratio is proposed and investigated. The main task for the model is to be a mean for determining the fuel optimal control signals, for each requested engine torque and speed.

Turbocharger testing is a time consuming process, and as rapid-prototyping technology advances, so must other areas in the development chain. As an example, in one study a compressor map took over 34 hours to measure. In this paper, an effort to combat the main bottleneck of turbocharger testing, namely the thermal inertia, is made. When changing operating point during the measurement process, several minutes can be required before the turbocharger components reach temperature steady state. In an earlier paper, a method based on non-linear trajectory optimization was developed that significantly reduced the testing time required to produce compressor performance maps. The time was reduced by a factor of over 60, compared to waiting for the system to reach steady state with constant inputs. However, the method required a model of the turbocharger. This paper extends the method with system identification and model predictive control (MPC).

Planning for charging in transport missions is vital when commercial long-haul vehicles are to be electrified. In this planning, accurate range prediction is essential so the trucks reach their destinations as planned. The rolling resistance significantly influences truck energy consumption, often considered a simple constant or a function of vehicle speed only. This is, however, a gross simplification, especially as the tire temperature has a significant impact. At 80 km/h, a cold tire can have three times higher rolling resistance than a warm tire. A temperature-dependent rolling resistance model is proposed. The model is based on thermal networks for the temperature at four places around the tire. The model is tuned and validated using rolling resistance, tire shoulder, and tire apex temperature measurements with a truck in a climate wind tunnel with ambient temperatures ranging from -30 to 25 °C at an 80 km/h constant speed.