Integrated OBD-II and direct controller area network access for vehicle monitoring system

The CAN (controller area network) bus is introduced as a multi-master, message broadcast system. The messages sent on the CAN are used to communicate state information, referred as a signal between different ECUs, which provides data consistency in every node of the system. OBD-II Dongles that are based on request and response method is the wide-spread solution for extracting sensor data from cars among researchers. Unfortunately, most of the past researches do not consider resolution and quantity of their input data extracted through OBD-II technology. The maximum feasible scan rate is only 9 queries per second which provide 8 data points per second with using ELM327 as well-known OBD-II dongle. This study aims to develop and design a programmable, and latency-sensitive vehicle data acquisition system that improves the modularity and flexibility to extract exact, trustworthy, and fresh car sensor data with higher frequency rates. Most of OBD-II dongles are based on very low capacity microcontroller hardware which cannot provide in-vehicle data processing, rather they transfer data to an external processing device. Furthermore, the researcher must break apart, thoroughly inspect, and observe the internal network of the vehicle, which may cause severe damages to the expensive ECUs of the vehicle due to intrinsic vulnerabilities of the CAN bus during initial research. Water coolant temperature, air temperature, and engine speed sensors signal were simulated and generated by using an ATmega8A. Desired sensors data were collected from various vehicles utilizing Raspberry Pi3 as computing and processing unit with using OBD (request–response) and direct CAN method at the same time. Two types of data were collected for this study. The first, CAN bus frame data that illustrates data collected for each line of hex data sent from an ECU and the second type is the OBD data that represents some limited data that is requested from ECU under standard condition. On the implementation of the above methods, this dissertation explores the differences between CAN and OBD data by integrating all these methods into one disposable GUI. A comparison has been done between OBD and CAN data to show how the number of data gathering measurement points of desired sensors can be improved to 15 data points per second through applying the proposed approach as compared to the standard OBD (request-response) method. The results have shown by using direct CAN method 25 data points per second for the essential sensors is achieved. The proposed system is reconfigurable, human-readable and multi-task telematics device that can be fitted into any vehicle with minimum effort and minimum time lag in the data extraction process. The standard operational procedure experimental vehicle network test bench is developed and can be used for future vehicle network testing experiment.

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