A combustion engine generates a lot of heat which need to be cooled to prevent damages to the engine and the surrounding parts. If the cooling system can not provide enough cooling to keep the engine in a well defined range of temperatures performance and durability will decrease and emissions increase. It is also important that the cooling system do not over-cool the engine, since this may result in rough running, increased engine friction and an overall negative performance. The aim of this thesis work is to create a complete 3D digital model of the cooling system for the first generation VED4 HP with CFD in STAR-CCM+. The simulated results are compared to available experimental data for validation. Today the entire system is being modeled with 1D CFD. One of the selected components in the cooling system being model in 3D at Volvo Cars is the water jacket. The 3D CFD model depends on the 1D CFD model for the boundary conditions which is an ineffective and time consuming process, sending data back and forth between the models when making changes. A 3D CFD model is not only more accurate than the 1D CFD model, since it capture the 3D flow phenomenas but it also allows parts or areas to be studied in detail. A study of four different turbulence models is conducted on the water jacket and on an arbitrary pipe in the cooling system. A mesh study is carried on the water jacket, the same arbitrary pipe and on the thermostat, both for the opened and closed thermostat. These studies are done with regard to pressure drop only. The study yields a low Reynolds model with the k-ε v2f turbulence model gave the best results. There is a discrepancy between the simulated results and the experiments. Main reasons to this may be the difference in the geometry used in this thesis for the digital model and the geometry used for the experiments together with the inaccuracies in the experimental data. The overall deviation is larger for a case with closed thermostat than for a case with an open thermostat. With the correct geometry and more accurate experimental data the simulations should be a close representation of reality.

Fuel consumption reduction is one of the main challenges in the automotiveindustry due to its economical and environmental impacts as well as legalregulations. While fuel consumption reduction is important for all vehicles,it has larger benefits for commercial ones due to their long operational timesand much higher fuel consumption. Optimal control of multiple energy buffers within the vehicle proves aneffective approach for reducing energy consumption. Energy is temporarilystored in a buffer when its cost is small and released when it is relativelyexpensive. An example of an energy buffer is the vehicle body. Before goingup a hill, the vehicle can accelerate to increase its kinetic energy, which canthen be consumed on the uphill stretch to reduce the engine load. The simplestrategy proves effective for reducing fuel consumption. The thesis generalizes the energy buffer concept to various vehicular componentswith distinct physical disciplines so that they share the same modelstructure reflecting energy flow. The thesis furthermore improves widely appliedcontrol methods and apply them to new applications. The contribution of the thesis can be summarized as follows: • Developing a new function to make the equivalent consumption minimizationstrategy (ECMS) controller (which is one of the well-knownoptimal energy management methods in hybrid electric vehicles (HEVs))more robust. • Developing an integrated controller to optimize torque split and gearnumber simultaneously for both reducing fuel consumption and improvingdrivability of HEVs. • Developing a one-step prediction control method for improving the gearchanging decision. • Studying the potential fuel efficiency improvement of using electromechanicalbrake (EMB) on a hybrid electric city bus. • Evaluating the potential improvement of fuel economy of the electricallyactuated engine cooling system through the off-line global optimizationmethod. • Developing a linear time variant model predictive controller (LTV-MPC)for the real-time control of the electric engine cooling system of heavytrucks and implementing it on a real truck. / <p>QC 20160128</p>

The global greenhouse gas CO2 emission from the transportation sector is very significant. To reduce this gas emission, EU has set an average target of not more than 95 CO2/km for new passenger cars by the year 2020. A great reduction is still required to achieve the CO2 emission target in 2020, and many different approaches are being considered. This thesis focuses on the thermal management of the engine as an area that promise significant improvement of fuel efficiency with relatively small changes. The review of the literature shows that thermal management can improve engine efficiency through the friction reduction, improved air-fuel mixing, reduced heat loss, increased engine volumetric efficiency, suppressed knock, reduce radiator fan speed and reduction of other toxic emissions such as CO, HC and NOx. Like heat loss and friction, most emissions can be reduced in high temperature condition, but this may lead to poor volumetric efficiency and make the engine more prone to knock. The temperature trade-off study is conducted in simulation using a GT-SUITE engine model coupled with the FE in-cylinder wall structure and cooling system. The result is a map of the best operating temperature over engine speed and load. To quantify the benefit of this map, eight driving styles from the legislative and research test cycles are being compared using an immediate application of the optimal temperature, and significant improvements are found for urban style driving, while operation at higher load (motorway style driving) shows only small efficiency gains. The fuel consumption saving predicted in the urban style of driving is more than 4%. This assess the chance of following the temperature set point over a cycle, the temperature reference is analysed for all eight types of drive cycles using autocorrelation, lag plot and power spectral density. The analysis consistently shows that the highest volatility is recorded in the Artemis Urban Drive Cycle: the autocorrelation disappears after only 5.4 seconds, while the power spectral density shows a drop off around 0.09Hz. This means fast control action is required to implement the optimal temperature before it changes again. Model Predictive Control (MPC) is an optimal controller with a receding horizon, and it is well known for its ability to handle multivariable control problems for linear systems with input and state limits. The MPC controller can anticipate future events and can take control actions accordingly, especially if disturbances are known in advance. The main difficulty when applying MPC to thermal management is the non-linearity caused by changes in flow rate. Manipulating both the water pump and valve improves the control authority, but it also amplifies the nonlinearity of the system. Common linearization approaches like Jacobian Linearization around one or several operating points are tested, by found to be only moderately successful. Instead, a novel approach is pursued using feedback linearization of the plant model. This uses an algebraic transformation of the plant inputs to turn the nonlinear systems dynamics into a fully or predominantly linear system. The MPC controller can work with the linear model, while the actual control inputs are found using an inverse transformation. The Feedback Linearization MPC of the cooling system model is implemented and testing using MathWork Simulink®. The process includes the model transformation approach, model fitting, the transformation of the constraints and the tuning of the MPC controller. The simulation shows good temperature tracking performance, and this demonstrates that a MPC controller with feedback linearization is a suitable approach to thermal management. The controller strategy is then validated in a test rig replicating an actual engine cooling system. The new MPC controller is again evaluated over the eight driving cycles. The average water pump speed is reduced by 9.1% compared to the conventional cooling system, while maintaining good temperature tracking. The controller performance further improves with future disturbance anticipation by 20.5% for the temperature tracking (calculated by RMSE), 6.8% reduction of the average water pump speed, 47.3% reduction of the average valve movement and 34.0% reduction of the average radiator fan speed.

Master of Science / Department of Mechanical and Nuclear Engineering / Kirby S. Chapman / The purpose of this thesis is to present on the development and results of the cooling system logic tree and model developed as part of the Pipeline Research Council International, Inc (PRCI) funded project at the Kansas State National Gas Machinery Laboratory. PRCI noticed that many of the legacy engines utilized in the natural gas transmission industry were plagued by cooling system problems. As such, a need existed to better understand the heat transfer mechanisms from the combusting gases to the cooling water, and then from the cooling water to the environment. To meet this need, a logic tree was developed to provide guidance on how to balance and identify problems within the cooling system and schedule appropriate maintenance. Utilizing information taken from OEM operating guides, a cooling system model was developed to supplement the logic tree in providing further guidance and understanding of cooling system operation. The cooling system model calculates the heat loads experienced within the engine cooling system, the pressures within the system, and the temperatures exiting the cooling equipment. The cooling system engineering model was developed based upon the fluid dynamics, thermodynamics, and heat transfer experienced by the coolant within the system. The inputs of the model are familiar to the operating companies and include the characteristics of the engine and coolant piping system, coolant chemistry, and engine oil system characteristics. Included in the model are the various components that collectively comprise the engine cooling system, including the water cooling pump, aftercooler, surge tank, fin-fan units, and oil cooler. The results of the Excel-based model were then compared to available field data to determine the validity of the model. The cooling system model was then used to conduct a parametric investigation of various operating conditions including part vs. full load and engine speed, turbocharger performance, and changes in ambient conditions. The results of this parametric investigation are summarized as charts and tables that are presented as part of this thesis.

The high complexity of vehicle front-end design, arising from considerations of aerodynamics, safety and styling, causes the airflow velocity profile at the radiator face to be highly distorted, leading to potentially reduced airflow volume for heat dissipation. A flow visualisation study showed that the bumper bar significantly influenced the cooling airflow, leading to three-dimensional vortices in its wake and generating an area of relatively low velocity across at least one third of the radiator core. Since repeatability and accuracy of on-road testing are prejudiced by weather conditions, wind-tunnel testing is often preferred to solve cooling airflow problems. However, there are constraints that limit the accuracy of reproducing on-road cooling performance from wind-tunnel simulations. These constraints included inability to simulate atmospheric conditions, limited tunnel test section sizes (blockage effects) and lack of ground effect simulations. The work presented in this thesis involved use of on-road and wind-tunnel tests to investigate the effects of most common constraints present in wind tunnels on accuracy of the simulations of engine cooling performance and radiator airflow profiles. To aid this investigation, an experimental technique for quantifying radiator airflow velocity distribution and an analytical model for predicting the heat dissipation rate of a radiator were developed. A four-hole dynamic pressure probe (TFI Cobra probe) was also used to document flow fields in proximity to a section of radiator core in a wind tunnel in order to investigate the effect of airflow maldistribution on radiator heat-transfer performance. In order to cope with the inability to simulate ambient temperature, the technique of Specific Dissipation (SD) was used, which had previously been shown to overcome this problem.