裝配圖大學生方程式賽車設計（模具及卡具設計）（有cad圖+三維圖）

裝配圖大學生方程式賽車設計（模具及卡具設計）（有cad圖+三維圖）,裝配,大學生,方程式賽車,設計,模具,卡具,cad,三維 Int J Adv Manuf Technol (2010) 51:233–246 DOI 10.1007/s00170-010-2626-2 ORIGINAL ARTICLE Development of an automated testing system for vehicle infotainment system Yingping Huang & Ross McMurran & Mark Amor-Segan & Gunwant Dhadyalla & R. Peter Jones & Peter Bennett & Alexandros Mouzakitis & Jan Kieloch Received: 18 December 2009 / Accepted: 12 March 2010 / Published online: 15 April 2010 # Springer-Verlag London Limited 2010 Abstract A current premium vehicle is implemented with a variety of information, entertainment, and communication functions, which are generally referred as an infotainment system. During vehicle development, testing of the info- tainment system at an overall level is conventionally carried out manually by an expert who can observe at a customer level. This approach has significant limitations with regard to test coverage and effectiveness due to the complexity of the system functions and human’s capability. Hence, it is highly demanded by car manufacturers for an automated infotainment testing system, which replicates a human expert encompassing relevant sensory modalities relating to control (i.e., touch) and observation (i.e., sight and sound) of the system under test. This paper describes the design, development, and evaluation of such a system that consists of simulation of vehicle network, vision-based inspection, automated navigation of features, random cranking waveform generation, sound detection, and test automation. The system developed is able to: stimulate a vehicle system across a wide variety of initialisation conditions, exercise each function, check for system responses, and record failure situations for post-testing analysis. Y. Huang (*) : R. McMurran : M. Amor-Segan : G. Dhadyalla Warwick Manufacturing Group, University of Warwick, Coventry CV4 7AL, UK e-mail: yingping.huang@warwick.ac.uk R. P. Jones School of Engineering and IARC, University of Warwick, Coventry, UK P. Bennett : A. Mouzakitis : J. Kieloch Jaguar Land Rover, Engineering Centre, Coventry, UK  Keywords Automatic testing . Infotainment . Image processing . Modeling and simulation . Hardware-in-the-loop . Robustness . Validation 1 Introduction An infotainment system provides a variety of information, entertainment, and communication functions to a vehicle’s driver and passengers. Typical functions are route guidance, audio entertainment such as radio and CD playback, video entertainment such as TV and interface to mobile phones, as well as the related interface functions for the users to control the system. There has been a large growth in this area driven by rapid developments in consumer electronics and the customer expectations to have these functions in their vehicles. Examples of this are surround sound, DVD entertainment systems, iPod connectivity, digital radio and television, and voice activation. With this growth in features there has been a corresponding increase in the technical complexity of systems. In a current premium vehicle, the infotainment system is typically implemented as a distributed system consisting of a number of modules communicating via a high speed fiber optic network such as Media Orientated Systems Transport (MOST). In this implementation the infotainment system is in fact a System of Systems (SOS) with individual systems having autonomy to achieve their function, but sharing resources such as the Human–Machine Interface (HMI), speakers, and communication channel [1]. Typical issues with such SOS are emergent behavior as systems interact in an unanticipated manner particularly during some initialisation conditions where it may be possible to get delays and failures in individual systems. These may not be readily observable until the particular part of the 234 system is exercised. During vehicle development, valida- tion of the infotainment system is extremely important and is conventionally carried out manually by engineers who can observe at a customer level but this has limitations with regard to test coverage and effectiveness. The first limitation is the time available to do manual tests, which is constrained by the development time scale and engineer’s working hours. The second is in the repeatability of the test, which is subject to human error. Hence, there is a requirement for an automated infotainment test capability, which replicates a human expert encompassing relevant sensory modalities relating to control (i.e., touch and voice) and observation (i.e., sight and sound) of the system under test. This test capability must be able to stimulate the system across a wide variety of initialisation conditions including those seen under cranking, low battery or fault conditions, exercise each function, check for system responses, and record related data, e.g., MOST bus trace, in the case of a malfunction for subsequent analysis. This paper describes the design and development of such a system as part of a UK academic and industrial collabora- tive project into the validation of complex systems. In the system, a Hardware-in-the-Loop (HIL) platform supported by a model-based approach simulates the vehicle network in real time and dynamically provides various essential signals to the infotainment system under test. Since the responses of the system are majorly reflected in the display of the touch screen, a machine vision system is employed to monitor the screen for inspection of the correctness of the patterns, text, and warning lights/tell-tales. The majority of infotainment functions are accessed by the user through an integrated touch screen. In order to achieve a fully automated testing, a novel resistance simulation technique is designed to simulate the operation of the touch screen. It is known that voltage transient processes, such as engine start where an instantaneous current inrush can reach 800 A, may result in some failures on the system. To test the system robustness against low voltage transient conditions, a transient waveform generator is developed to mimic three specific transient processes. A testing automation software integrates and controls all devices to form a fully automated test process, which can be run continuously over days or even weeks. The developed testing system not only makes various testing possible, repeatable, and robust, but also greatly improves testing efficiency and eases the task of tedious validation testing. Model-based testing of functionality of an Electronic Control Unit (ECU) using HIL has been implemented by automotive manufacturers over the last few years [2–5]. Currently, Jaguar Land Rover (JLR) has adopted the HIL technology for automated testing and validation of elec- tronic body systems, powertrain, and chassis control systems [6, 7]. The benefits of this technology include  Int J Adv Manuf Technol (2010) 51:233–246 automated testing, earlier testing before physical prototype vehicle build, ability to perform robustness and dynamic testing, and reduction of supplier software iterations. Machine vision systems have been used in many manufac- turing applications such as automotive [8–10], robotic guidance [11], and tracing soldering defects [12, 13]. The author also employed machine vision technology for obstacle detection in advanced driver assistant systems [14, 15]. However, no research has been reported using a machine vision system for design validation testing. Validation testing in the design stage is very much different from testing in manufacturing. Firstly, design validation testing requires diverse test cases covering a large number of, rather than a restricted, set to prove proper design. The only way to generate the test cases when the car is in the early development phases is using model-based testing techniques, which simulate vehicle-operating conditions in real time. Secondly, design validation testing requires iterative and repeated tests for robustness evaluation, although it does not require a high volume of parts to be tested. Thirdly, design validation testing needs frequent adaptation of the testing system for different types of cars or for different development stages of the same car. One novelty of this paper is the integration of the machine vision and HIL techniques for complex design validation testing. In addition, the paper proposes a novel pseudo- random concept for generating three voltage transient waveforms, which allows the testing to mimic the random process as seen in real cases, and also enables the testing to be regenerated for further investigations. Furthermore, a common approach to mimic the operation of the touch screen by a human is by using robot arms. In this design, a crafty resistance simulation approach replaces the robot arms to achieve the goal. The approach can be completely implemented in software by using the HIL simulator, therefore eliminating the need of complicated mechanical devices such as robot arms, pneumatic/hydraulic, and solenoid actuators. 2 System configurations The configuration of the system developed for testing the infotainment system is shown in Fig. 1. The system consists of six vital elements including the unit under test, HIL tester, machine vision (camera), operation of the touch screen, transient waveform generator, and test automation. The infotainment system under test consists of a number of modules including the radio/CD player, amplifier (AMP), navigation system, blue tooth/telephone/USB, vehicle setup, auxiliary audio interface, and climate control functions. The HMI is based primarily on a 7″ TFT resistive touch screen with additional hard keys on an Integrated Int J Adv Manuf Technol (2010) 51:233–246 Images (referenced to test) Ethernet  RS232 Serial  Camera  235 Vision Test Trigger Test Results Control Parameters  HIL Tester  Resistive control of touch screen Host PC  Optical  CAN Touch Screen Capture Data Test Automation scripts Test Script Precondition….test….post condition Precondition….test….post condition Trigger Low Voltage test profile RS232  ICP & Remote Cont  Climate/Setu p/Interface ICM gateway Precondition….test….post condition Precondition….test….post condition Precondition….test….post.test….post condition ………………………. Precondition .test….post condition Precondition .test….post condition Precondition .test….post condition Power Supply  Radio/CD player  MOST Ring  Optolyser analyzer Precondition .test….post condition …………………….… Blue tooth/ MOST Analyzer trigger Fig. 1 System configuration Transient waveform generator Audio output monitoring Navigation  AMP Phone/USB Control Panel (ICP) in the center console and remote controls on the steering wheel. Audio output is via a DSP amplifier. Communication between the modules is through a MOST optical bus carrying control, data, and audio information. The infotainment system is connected to the rest of the vehicle via a module called ICM acting as a gateway between MOST and a vehicle Controller Area Network (CAN) bus. It is worth noting that the ICP and the remote controls on the steering wheel reside in the vehicle CAN bus. In addition, a MOST analyzer was connected in the MOST ring during the testing. The MOST analyzer was controlled by the HIL tester via digital outputs to trigger the logging of the MOST traces when a failure occurs. Within the testing system, the HIL tester simulates the vehicle network and dynamically provides various essential signals to the infotainment system under test. It also acts as a control center to control other devices. For example, it sends commands via a serial port to trigger the camera and receive the inspection results from the camera. The machine vision system (camera) checks the responses of the system by monitoring the display of the touch screen such as patterns and text. The operation of the touch screen is achieved by using a resistance simulation approach, which is imple- mented in the HIL tester. By using this approach, the testing system can get access to the majority of infotainment  functions. The transient waveform generator produces voltage signals and powers up the infotainment system via a programmable power supplier. The waveform generator, mimicking three voltage transient processes, is used for testing system robustness against low voltage events. The test automation is running in the host computer to integrate and control all devices to form a fully automated test process. In addition, the host PC has been linked with the machine vision system via a TCP/IP Ethernet communica- tion. This link allows the storage of time-stamped images in the host PC so that the behavior of the unit under test can be reviewed offline in terms of the test results. The following sections describe the individual elements of the automated testing system including the HIL tester, vision-based inspection, automated touch screen operation, transient waveform generator, and test experiments. 3 HIL tester A dSPACE simulator [16] was used to form a hardware-in- the-loop simulation test system. The HIL test system simulates the vehicle CAN bus to provide power mode signals to the MOST Network via the MOST gateway. It also simulates the ICP to operate the infotainment system. Test Results condition … … … MOST … 236  Int J Adv Manuf Technol (2010) 51:233–246 Fig. 2 dSPACE real-time simulator Simulation Models Expansion box Simulation of Power Mode and integrated control panel - CAN Digital signal processor Power supply control Simulation of touch Screen operation and On/Off Switches -resistance outputs Sound detection and measuring sound frequency – A/D inputs Serial communications RS232 Real-time simulator  Standard I/O Interface CAN I/O RS232 In addition, the HIL tester also provides RS 232 serial interfaces to communicate with the camera and transient waveform generator, resistance simulation to operate the touch screen, and an A/D interface for detecting sound and measuring sound frequency. The dSPACE Simulator consists of simulation models and expansion hardware as shown in Fig. 2. The expansion box includes one processor board DS1006 and one interface board DS2211. The DSP board runs the simulation models, while the interface board provides various interface links with other devices, such as CAN, resistance outputs, A/D converters, analog/digital input and output, and RS 232 serial communication to control the machine vision system. In the HIL system, simulation models are implemented in MATLAB/Simulink/Stateflows and compiled using the auto-C-code generation functions of Matlab’s Real-Time Workshop for real-time execution. 3.1 Simulation of power mode The behavior of the components of the Infotainment system is determined by a CAN signal known as ‘Power mode,’ which indicates the operational state of the vehicle e.g., ‘ignition off,’ ‘ignition on,’ ‘engine cranking,’ ‘engine running,’ etc. To test the performance of the infotainment system under cranking conditions, the car under test must be in the ‘engine-cranking’ state when applying cranking transient voltages to the car. Moreover, any subsequent functional tests must be conducted in the ‘engine-running’ state after the cranking. In a real car, power mode messages are transmitted by the body ECU connected to the CAN. Since we were testing the infotainment system on a test  platform representing a real car sometimes, in order to generate the correct power mode behavior, we utilized CAN simulation of the HIL tester to simulate the body ECU to transmit power mode messages to the MOST gateway. 3.2 ICP simulation The Integrated Control Panel of the infotainment system provides users with a number of hard keys for operating the system. The functions controlled by the ICP include selection of the audio sources, loading and ejecting CDs, seeking up/down for radio stations and CD tracks, volume controls, and so on. To enable an automated testing of these functions, the ICP must be controlled by the test center, the dSPACE real-time simulator. The ICP electronic control unit interfaces with a vehicle via the vehicle CAN. Therefore, the ICP unit was simulated by using the CAN simulation of the dSPACE simulator. The models of ICP simulation are shown in Fig. 3. 3.3 Sound detection Sound detection contains two aspects i.e., detecting sound on or off and detecting the frequency (dominant) of the sound. The sound signal is sampled from the speaker end as shown in Fig. 1, and converted into digital signal by an A/D converter within the dSPACE simulator. The sound on/off is determined by checking the amplitude of the signal. The frequency of the sound is detected by the specific circuit of the simulator. The purpose of detecting sound frequency is to identify a sound source and active CD track. The model is shown in Fig. 4. Int J Adv Manuf Technol (2010) 51:233–246 Fig. 3 Model of ICP simulation 3.4 Simulation of serial communications The RS232 serial communication is used to establish the link between the HIL tester with the camera and the transient waveform generator so that closed loop testing can be performed. During the test, the HIL tester is the control center to command the camera and the transient waveform generator and to obtain the inspection results from them. For example, the camera needs to be commanded to select a specific image processing job file for specific testing. The checking results generated by the camera need to be returned to the HIL tester. The transient waveform generator needs to be com-  237 manded to generate a specific cranking waveform for specific testing. The parameters of the waveform resulting in a failure need to be returned to the HIL tester so that this specific testing can be duplicated in the later analysis stages. A simplified version of the simulation models of the RS232 serial communication is shown in Fig. 5. A transmitted message is ended with a carriage return and has a maximum length of 10 bytes. A received message has a fixed length of 8 bytes. The first 3 bytes gives the result name while the following 5 bytes indicates the result values. For example, the active track number is abbreviated as the result name ATN. 238 Fig. 4 Model of sound detection 4 Vision-based inspection 4.1 Machine vision system The machine vision system consists of a camera, lighting, optics, and image processing software. A Cognex In-sight color vision sensor [17] was selected for image acquisition and processing, which offers a resolution of 640×480 pixels and a 32-MB flash memory. The acquisition rate of the vision sensor is 60 full frames per second. The image acquisition is through progressive scanning. The image processing software (In-sight Explorer Ver 4.2.0) provides a wide library of vision tools for feature identification, verification, measurement, and testing applications. The PatMaxTM technology for part fixturing and advanced Optical Character Recognition (OCR) tools for reading texts [17] are available within the software. The primary source of illumination is