FEATURE CAD/DESIGN SOFTWARE


Go with the flow during race car design When developing their race car for the Formula Student event, Team Bath Racing


chose Simcenter Flomaster software to help solve the complex engineering challenges. Here, Siemens Digital Industries Software talks us through the application


F


or the annual Formula Student competition, undergraduate engineering students design and


build a single-seat, open-wheeled, race car. Team Bath Racing from the University of Bath is the most successful Formula Student team in the UK. Marios Mouzouras, a member of Team Bath Racing for the 2016 season, explained that they started working on the project as third year students. He said: “We worked as a team to design a race car from scratch as part of a design and business project that contributes to our degrees. We then take these designs to compete in the Class 2 design event at Silverstone racetrack in the UK, where lessons learned are used to develop the design further. As we enter our final year of engineering study, manufacture of the car begins and we watch our designs become a reality.” So when it came to designing the thermal


management system, the team decided to use Simcenter Flomaster software, a system-level thermo-fluid simulation tool that virtually simulates and optimises fluid flow in order to improve system performance. The goal was to use it to create a representative transient thermal model of the vehicle’s cooling and lubrication system which would include the engine, turbocharger, radiators, pumps, piping, header tanks, oil cooler and fans. To start with, the team set maximum temperature boundary conditions


and then conducted several experiments to obtain the necessary inputs for the transient model. They performed tests using an in-house dynamometer to quantify the heat transfers occurring at each engine revolution per minute (RPM) and torque, then conducted an outdoor air flow test to determine the relationship between the air flow through the radiators and the vehicle’s speed with fans on or off. Finally, the team did a coast-down test to determine the vehicle rolling and drag resistance coefficient to develop an engine torque model to match the engine heat transfer against torque during vehicle operation. Results of these tests were used in the creation of the thermal model. Using these, the next step was to create a radiator model in the software using both the fin and tube geometry of the radiator and the performance data provided by the manufacturer. Mouzouras explained: “Comparing simulation results and test data showed


a good response with a change in coolant flow rate but had an increasing discrepancy with an increase in air flow velocity.” This discrepancy was mostly likely caused by error with the longitudinal and transverse pitch of the tubes stating that the values are very small. The team tested values for different pitches and realised that as the values decreased, the heat rejections increased. So, they experimented with additional simulations, switching from cross-flow heat exchangers to other heat exchanger models in Simcenter Flomaster, obtaining the best results using the thermal heat exchanger model that had a 1.13% error compared to actual data. The trends when increasing coolant flow rate or air flow rates were


both as expected. There were small differences at the 6-10m/s air flow velocities, because the fixed time step for the air mass flow gave a maximum of 0.005kg/s difference between modelled and actual. It was also important to test the pressure losses. There was an anomalous


change in pressure drop observed from the experimental data. In the experimental case of 2m/s of air flow, the pressure drops from 54.91kPa to 52.33kPa with an increase in coolant flow rate, and then starts increasing with high air flow rates. This was not captured by the


28 SEPTEMBER 2020 | DESIGN SOLUTIONS Team Bath Racing’s


transient model schematic in Simcenter Flomaster


model which instead predicted a constant increase as flow rates increased, which followed the rest of the data sets as expected. A similar accuracy was observed on the coolant side, with an increase


in pressure drop with an increase in coolant flow rates. For constant coolant flow rates, the pressure drop for the actual data increased with an increase in air flow velocity, whereas for the model the opposite was happening but at a much smaller rate. Overall, the heat duties and pressure drops had a very small error


between the modelled and actual data. The heat duty’s maximum error was 1.12% while, for the pressure drops, the maximum error was 7.6%. With the radiator model completed, the team modelled the rest of


the components using a combination of experimental data obtained through testing and logged data from the previous year’s endurance event at Silverstone. This included crucial information such as engine RPM, vehicle speed and time.


MODELLING AND VALIDATION Team Bath Racing’s 2016 car was first modelled and validated using the coolant temperatures logged from the event. The maximum coolant temperature was matched with the time needed for the coolant to reach a steady-state. One difference was a slight variation in the rate at which the coolant’s temperature increases. However, halfway through the endurance race, there is a compulsory engine shut-down period where there is a driver change. No coolant temperature data was logged during that period, but the model predicted a larger temperature drop. This proved that the model is reliable and can be used to simulate future cars’ cooling and lubrication systems. Tests were also completed to optimise the system – including testing


various radiator core sizes at different ambient temperatures; running with a single radiator instead of two; having an unexpected broken radiator during the endurance race; checking different size oil coolers and their positions in the cooling system; fan sizing; electric water pump sizing; pipe diameter selection; and some control strategies.


Siemens Digital Industries Software www.sw.siemens.com / DESIGNSOLUTIONS


Page 1  |  Page 2  |  Page 3  |  Page 4  |  Page 5  |  Page 6  |  Page 7  |  Page 8  |  Page 9  |  Page 10  |  Page 11  |  Page 12  |  Page 13  |  Page 14  |  Page 15  |  Page 16  |  Page 17  |  Page 18  |  Page 19  |  Page 20  |  Page 21  |  Page 22  |  Page 23  |  Page 24  |  Page 25  |  Page 26  |  Page 27  |  Page 28  |  Page 29  |  Page 30  |  Page 31  |  Page 32  |  Page 33  |  Page 34  |  Page 35  |  Page 36  |  Page 37  |  Page 38  |  Page 39  |  Page 40  |  Page 41  |  Page 42  |  Page 43  |  Page 44