Recommendation for future work

The primary goal of this project has been to develop a control system for automatic adjustment of articulated truck’s cab roof deflectors. The research objectives for the development of the control system were fulfilled, but the system has some limitations that could not be addressed within the project timeframe. The system itself works as it was designed, but the electronic components are only suitable for a prototype in laboratory conditions. Before the system can be tested in real application the following issues need to be addressed and improved:

- The available deflector is sufficient for a working prototype. Its make is applicable for

of a universally applicable automated CRD is taken forward it is recommended to redesign the deflector for a compatibility with a wider range of truck-trailer combinations.

- The CFD simulations that have been run allowed the development of a functional

concept for CRD optimum position calculation that is applicable for microcontrollers with limited computing power. If the idea of an universally applicable automated CRD is taken forward the equations for the optimum deflector position calculation have to be recompiled. To do so also the set of CFD simulations with changed deflector geometry has to be run again.

- The aerodynamic model that has been developed allows to precisely calculate the

optimum deflector position. This project has shown that the stream/vehicle velocity has no impact on the optimum deflector position for the CRD setup used. For further work it is recommended to expand the number of simulations for velocities lower than 40 mph and higher than 56 mph to get more precise optimum positions for crosswind situations.

- The sensors and the PCB for this project have been developed for laboratory conditions.

The system performance test was successful and has shown the expected results. Taking the project forward requires changes in both sensor array and control system to sustain harsh environmental conditions such as rain and changing temperature conditions. Therefore all employed sensors have to be reviewed and are likely to be replaced in this process.

- A validity check of the initial CFD results that were used in this project brought up, that

the CFD results might be faulty. These faulty CFD results might affect the performance of the system, since these simulation results do not match with the results of a real world application. The developed algorithm for data processing and the functionality of the developed control system is not affected by faulty simulation results. Though it is recommended to rerun the CFD simulations once the fault has been located and fixed. To update the system with the improved data the improved CFD results have to be processed into vector equations as described in chapter 5.1.3.4. The new parameters (Tables 5-2 to 5-4) have to be changed in the controller software. The modular approach of a core software and an independent config file makes the system easy to adapt for

changing geometries or changing CFD results. Changing the equations for the calculation of the optimum deflector position (Tables 5-2 to 5-4) in the config file will update the software to the new CFD results. The representation of the parameter tables in the config file can be found in Appendix A4 p. 155.

Chapter 6 has shown that the developed system is operational and performes well as an operational prototype. During the development of the system and the process of testing and debugging some issues and ideas for improvement came up that would require a complete redesign of the control system and its software or could not be made in time.

- The calculation of the wind vector information is proven good earlier but it contains

two types of error. One error is based on the precision of the calibration parameters and is known from chapter 3.7. The other error results from the acquisition of the pressure sensor outputs. The pressure sensor outputs are read sequentially instead of simultaneous. This is because the pressure sensor outputs are interfaced directly to the ADC of the microcontroller. This issue can be improved by employing latching the sensor output signals before reading the signals into the controller. Alternatively a microcontroller could be used that has a latching component built in.

- The timer interval for triggering the sensor output acquisition has been set to a default

value representing 500 ms (Chapter. 5.1.1). It is recommended to modulate the timer value with respect to the recurrence interval and the execution time of the wind calculation algorithm. The execution time can be found by implementing an output toggle command at the end of case 6 in the “ADC conversion completed” interrupt (Appendix A4 p. 126). The recurrence interval of the controller software can be calculated from the generated frequency on the toggle output. The timer interval for the sensor output acquisition can be adjusted accordingly.

- If the timer interval is adjusted to the recurrence interval of the controller software

controller sleep modes can be used to reduce power consumption of the controller in operation. To do so the controller sleep mode [32, p. 46-50] has to be configured within the configuration section of the controller software (Chapter 5.1.1) and is activated at in the endless loop main routine. Exact timer interval triggering and sleep modes enable an exact timing of the controller software according to the application.

- If the measured recurrence interval of the controller software is found to slow for the

application (for example with desired higher precision in the deflector positioning and therefore required higher measuring interval) it might be necessary to change the microcontroller. The used AT90CAN128 8-Bit controller does not feature a floating point calculation unit (FPU). The lack of a FPU requires the software compiler to compile floating point calculations to be executed with the logical unit of the microcontroller. This workaround in the compiler leads to a significantly increased calculation time for floating point calculations compared to calculation time with a controller that features a FPU. Applicable controllers that feature a FPU are likely to be ARM chip architecture controllers. Changing the controller architecture to ARM with FPU requires a full revision of the controller software and controller board but offers significant improvement in floating point calculation performance.