In this study, CFD simulations of a complete truck are carried out to investigate the effect of altered simulation settings at cold climatic conditions. The aim of this study is to obtain knowledge through CFD simulations performed on a selected driving condition namely at a vehicle speed of 93 kph, an ambient temperature of -20 °C and for an engine operating at 25 % load. Data from measurement carried out in a climatic wind tunnel is available and utilized as boundary conditions for the simulations.The simulations are performed under steady state conditions utilizing the commercial software STAR-CCM+. The first simulation case (reference simulation case) is constructed through java macro-scripts as per the standard VTM settings at Scania. The results from the simulations are compared with the measurement data utilizing temperature validation probes. These probes are located around the engine and measure the air temperature in the underhood engine compartment. The results from the first simulation case show that the temperature of each probe located in front of the engine and above the engine agrees well with the measured probe temperatures. But the temperature of the remaining probes show larger differences with the measured probe temperatures. To investigate the larger differences in probe temperatures, additional simulations are carried out by changing specific simulation settings. For instance, this is achieved by including thermal radiation in the physics continua. Finally, a simulation of engine load of 100 % is carried out and the results from the simulation are compared with the measurement from the same engine load as well as the results from the measurement and simulation of 25 % engine load. The results from all the simulations indicate that additional boundaryconditions and/or different methodologies need to be explored to better replicate the cold climatic conditions in the simulations.

Safety, performance and driving comforts are given high importance while developing modern day cars. All-Wheel Drive vehicles are exactly designed to fulfill such requirements. In modern times, human concern towards depleting fossil fuels and cognizance of ecological issues have led to new innovations in the field of Automotive engineering. One such outcome of the above process is the birth of electrical hybrid vehicles. The product under investigation is a combination of all wheel drive and hybrid system. A superior fuel economy can be achieved using hybrid system and optimized vehicle dynamic forces are accomplished by torque vectoring action which in turn provides All-Wheel Drive capabilities. Heat generation is inevitable whenever there is a conversion of energy from one form into another. In this master thesis investigation, a thermal simulation model for the product is built using 1D simulation tool AMESim and validation is done against the vehicle driving test data. AMESim tool was chosen for its proven track record related to vehicle thermal management. The vehicle CAN data are handled in MATLAB. In a nutshell, Simulation model accounts for heat generation sources, oil flow paths, power loss modeling and heat transfer phenomena. The final simulation model should be able to predict the transient temperature evolution in the rear drive when the speed and torque of motor is supplied as input. This simulation model can efficiently predict temperature patterns at various locations such as casing, motor inner parts as well as coolant at different places. Various driving cases were tried as input including harsh (high torque, low speed) ones. Simulation models like this helps Engineers in trying out new cooling strategies. Flow path optimization, flow rate, convection area, coolant pump controlling etc are the few variables worth mentioning in this regard.

Transient vehicle thermal management simulations have the potential to be an important tool to ensure long component lifetimes in heavy-duty vehicles, as well as save development costs by reducing development time. Time-resolved computational fluid dynamics simulations of complete vehicles are however typically very computationally expensive, and approximation methods must be employed to keep computational costs and turn-around times at a reasonable level. In this thesis, two transient methods are used to simulate two important time-dependent scenarios for complete vehicles; hot shutdowns and long dynamic drive cycles. An approach using a time scaling between fluid solver and thermal solver is evaluated for a short drive cycle and heat soak. A quasi-transient method, utilizing limited steady-state computational fluid dynamics data repeatedly, is used for a long drive cycle. The simulation results are validated and compared with measurements from a climatic wind tunnel. The results indicate that the time-scaling approach is appropriate when boundary conditions are not changing rapidly. Heat-soak simulations show reasonable agreement between three cases with different thermal scale factors. The quasi-transient simulations suggest that complete vehicle simulations for durations of more than one hour are feasible. The quasi-transient results partly agree with measurements, although more component temperature measurements are required to fully validate the method.

Systematické řízení tepelných a elektrických toků v plně elektrických automobilech se stává velmi důležitým, protože v těchto typech automobilů není k dispozici dostatek odpadního tepla pro vytápění kabiny. Aby v zimním období nedocházelo ke snížení dojezdu, je nutné použití technologií, které umožní snížení spotřeby energie nutné k vytápění kabiny (např. tepelné čerpadlo, zásobník tepla). Je také zapotřebí vytvořit řídicí algoritmy pro tato zařízení, aby byl zajištěn jejich optimální provoz. V letním období je nezbytné řídit tepelné toky v rámci elektromobilu tak, aby nedocházelo k nadměrnému vybíjení baterie kvůli chlazení kabiny a dalších částí. Tato práce řeší jak návrh řídicích algoritmů, tak i vývoj rozhodovacího algoritmu, který zajistí směřování tepelných toků.