CAN Bus Research Articles

Enhancing Cyber Security in Autonomous Vehicles: A Hybrid XG Boost-Deep Learning Approach for Intrusion Detection in the CAN Bus

Enhancing Cyber Security in Autonomous Vehicles: A Hybrid XG Boost-Deep Learning Approach for Intrusion Detection in the CAN Bus

Lightweight MDSCA-Net: an end-to-end CAN bus fault diagnosis framework

Lightweight MDSCA-Net: an end-to-end CAN bus fault diagnosis framework

Virtual Analysis and Optimization of Fuel Consumption for Diesel-Powered Buses

In this study, fuel consumption test cycles and commonly used SORT cycles for buses were discussed. An exemplary bus model was extensively modeled in terms of power systems. In ad-dition to main components such as the engine, transmission, torque converter, and axle, the drags of engine-powered components such as alternators, engine cooling fan, and air conditioning compressor were integrated into the powertrain model to ensure that the calculated consumption comes as close as possible to the real-life values. The tire model, which determines the quality standard in vehicle simulation, was also discussed in detail. During the modeling of these components, necessary parameters were obtained through analyses and tests conducted on the sample vehicle using the CAN bus and added sensors. After the completion of the model, real-life tests were conducted to validate the virtual analysis results. Once the model was validated, virtual studies continued to reduce the vehicle's consumption. Particularly during these studies, reducing consumption and enhancing performance through automatic transmission optimization were emphasized. When virtual models validated with SORT simulations are optimized with route-specific virtual analysis, public vehicles will minimize environmental impacts by reducing carbon emissions and at the same time perform more efficiently.

Dynamic Modeling and Control Strategy Optimization of a Volkswagen Crafter Hybrid Electrified Powertrain

This article studies the transformation and assembly process of the Volkswagen (VW) Crafter from conventional to hybrid vehicle of the department of vehicles engineering, University of Debrecen, and uses a computer-aided simulation (CAS) to design the vehicle based on the real measurement data (hardware-in-the-loop, HIL method) obtained from an online CAN bus data measurement platform using MATLAB/Simulink/Simscape and LabVIEW software. The conventional vehicle powered by a 6-speed manual transmission and a 4-stroke, 2.0 Turbocharged Direct Injection Common Rail (TDI CR) Diesel engine and the transformed hybrid electrified powertrain are designed to compare performance. A novel methodology is introduced using Netcan plus 110 devices for the CAN bus analysis of the vehicle’s hybrid version. The acquired raw CAN data is analyzed using LabVIEW and decoded with the help of the database (DBC) file into physical values. A classical proportional integral derivative (PID) controller is utilized in the hybrid powertrain system to manage the vehicle consumption and CO2 emissions. However, the intricate nonlinearities and other external environments could make its performance unsatisfactory. This study develops the energy management strategies (EMSs) on the basis of enhanced proportional integral derivative-based genetic algorithm (GA-PID), and compares with proportional integral-based particle swarm optimization (PSO-PI) and fractional order proportional integral derivative (FOPID) controllers, regulating the vehicle speed, allocating optimal torque and speed to the motor and engine and reducing the fuel and energy consumption and the CO2 emissions. The integral time absolute error (ITAE) is proposed as a fitness function for the optimization. The GA-PID demonstrates superior performance, achieving energy efficiency of 90%, extending the battery pack range from 128.75 km to 185.3281 km and reducing the emissions to 74.79 gCO2/km. It outperforms the PSO-PI and FOPID strategies by consuming less battery and motor energy and achieving higher system efficiency.

A Wireless Ad Hoc Network Communication Platform and Data Transmission Strategies for Multi-Bus Instruments

As automatic test technology advances, the number of programmable instruments in a single test system increases. Traditional wired communication methods have a limited range and involve complex cable layouts. Single-function wireless converters provide a viable alternative, but they have limitations. These include complicated configuration, issues with multi-system collaboration, and data blocking. This paper proposes a wireless ad hoc network platform for multi-bus instruments based on a low-cost ESP-12H WiFi module. The platform supports GPIB, RS232, RS485, and CAN bus interface instrument access. It features easy configuration, ad hoc networking, and self-repairing capabilities. A relay multi-hop network with a tree topology expands capacity and coverage. Additionally, a dynamic window-receiving mode and an improved multi-priority queue ensure data transmission integrity. The experimental results show that the platform’s networking time is less than 10 s, and the coverage range reaches 50 m in complex indoor environments. It also shows good stability when running for a long time. However, due to hardware and software design limitations, the actual upload speeds fall short of the theoretical values. For example, RS232 and RS485 are about 10% slower than the theoretical values, and GPIB is about 80% slower. Further optimization is required in the future.

Synthetic data generation using Copula model and driving behavior analysis

In this study, the generation of synthetic driving data that can reflect real behavior well using the Copula model was investigated. To see the difference in behavior patterns in the generated synthetic driving data, a feature correlation comparison was made. The difference in driving behavior was provided with the K-means based classification model. It was shown that with a Random Forest model trained with synthetic data and having high accuracy, the privacy of real data could be protected by 98.55%. At the end of the study, it was seen that the Copula model could obtain synthetic driving data with sufficient accuracy with CAN bus data without additional sensor support.

The use of non-invasive tomographic imaging to monitor lung condition

The development of ultrasound tomography (UST) aimed to significantly enhance the precision and safety of non-invasive UST imaging, particularly for studying crystallization processes in biological tissues. The initiative sought to address the limitations of previous versions by incorporating advanced technological upgrades and providing a more user-friendly interface. The revised system comprises eight four-channel measurement cards interconnected via a high-speed FD CAN bus capable of 8 MBPS data transfer. Each card features a dedicated square wave generator, band-pass filters tailored to specific ultrasonic transducer frequencies, and a sophisticated signal envelope processing unit. The core processing unit is built around a 32-bit STM32G474RE microcontroller, ensuring robust data handling and image reconstruction capabilities. The UST device presented demonstrates improved image clarity and reduced noise interference. The measurement card redesign has achieved a sampling rate of 4 MBPS per channel and includes a two-stage amplification for dynamic range management. Upgraded power components, comprehensive shielding, and the integration of advanced analog switches have led to an enhanced signal-to-noise ratio, pivotal for high-resolution imaging. The advancements presented in the UST device mark a noteworthy progression in ultrasound imaging technology, extending beyond traditional applications. High-speed data collection, precise signal processing, and user-centered design have all come together to make a system that can image crystallization processes more accurately and accurately over and over again.

A Two-Layer Dynamic ECU Group Management Scheme for In-Vehicle CAN Bus

A Two-Layer Dynamic ECU Group Management Scheme for In-Vehicle CAN Bus

STM32 microcontroller and CAN bus based FSAE racing car electrical part design

A microcontroller is a kind of chip in integrated circuits, which is a device that integrates multiple components together to accomplish a certain function. Compared with the traditional digital module, the advantages of a microcontroller lie in smaller size, lower power consumption, and higher flexibility. Its performance and functionality of the expansion depend on the design and manufacturing process of integrated circuits, and the wide application of microcontrollers cannot be separated from the support of integrated circuits. With the continuous development of integrated circuits, the application of microcontrollers is also more and more extensive; in automotive electronics, industrial control, and embedded systems have been applied on a large scale. CAN bus is a kind of serial communication protocol used for communication between various electronic components in the vehicle. It is one of the most widely used communication buses in the world, and it has been applied on a large scale in the fields of the automotive industry, aerospace industry, industrial control, safety protection, and so on. Scale application. This paper mainly discusses the application of STM32 microcontrollers and their ability to bus in FSAE racing cars, the functions they can realize, and the enhancement of racing car performance.

A Multivariate Time Series Prediction Method for Automotive Controller Area Network Bus Data

This study addresses the prediction of CAN bus data, a lesser-explored aspect within unsupervised anomaly detection research. We propose the Fast-Gated Attention (FGA) Transformer, a novel approach designed for accurate and efficient prediction of CAN bus data. This model utilizes a cross-attention window to optimize computational scale and feature extraction, a gated single-head attention mechanism in place of multi-head attention, and shared parameters to minimize model size. Additionally, a generalized unbiased linear attention approximation technique speeds up attention block computation. On three datasets—Car-Hacking, SynCAN, and Automotive Sensors—the FGA Transformer achieves predicted root mean square errors of 1.86 × 10−3, 3.03 × 10−3, and 30.66 × 10−3, with processing speeds of 2178, 2768, and 3062 frames per second, respectively. The FGA Transformer provides the best or comparable accuracy with a speed improvement ranging from 6 to 170 times over existing methods, underscoring its potential for CAN bus data prediction.

Semi-empirical model for timber truck speed profile and fuel consumption

ABSTRACT This paper presents a semi-empirical model for driving speed simulation and estimation of energy use in timber trucks in Sweden. The model is composed of two parts; the first part takes as input road properties along a route and applies a kinematic model to simulate a driving pattern. The kinematic model contains parameters that are found statistically from large-scale recordings of CAN bus data from 21 timber trucks in 1 year. The second part applies a mechanistic model on the simulated speed profile to compute fuel use. The driving pattern simulator can predict the driving time and energy use with roughly the same variance as can be observed between different trucks and drivers following the same route. An average rolling resistance coefficient of 0.0068 was found from a coast-down study, but with substantial variation between vehicles.

A vehicle firmware security vulnerability: an IVI exploitation

In the last years, the increasing vehicular technology has led to a surge in cybersecurity attacks, particularly regarding connected vehicles and their vulnerable infotainment systems. This paper explores the vulnerabilities within an In-Vehicle Infotainment (IVI) system firmware, focusing on the Gen5W_L multimedia device utilized in Hyundai, Kia, and Genesis vehicles. Leveraging reverse engineering techniques, the study uncovers several security issues within the firmware, allowing for the creation and installation of custom firmware. The paper introduces Chimaera, a reverse engineering attack targeting the IVI system firmware, which exploits a printf vulnerability introduced by statically compiling the mbedtls library. After a reverse engineering analysis and injecting malicious assembly code directly in the IVI firmware, the attack enables the extraction of sensitive information from the firmware files like the cryptographic keys to install a customized firmware. The research shows that exploiting these vulnerabilities facilitates the installation of insecure firmware, granting attackers unauthorized access to vehicle functionalities. This includes the possibility to inject CAN bus messages, potentially compromising critical vehicle systems such as radio controls and safety features. The findings underscore the need for robust cybersecurity measures within automotive systems and highlight the significance of vulnerability assessment to mitigate security risks in connected vehicles.

A Sensor-Based Application for Eco-Driving Management in Short-Term Car Rentals

How to reduce fuel consumption to mitigate CO2 emissions to the atmosphere and improve road safety is one of the priorities to be addressed in the field of transport in the European Union. Considering the trend towards more frequent car rentals, it seems important to encourage drivers to change their driving style to a more ecological and economic one. This can be achieved by a system (built of a sensor located in the car, analytical software in the cloud and a mobile application for displaying results) that analyzes driving style and tells the driver how to drive better. Solutions such as the car bus PCB, GSM/GPS modem and 3D sensors were used in the development of the sensor. The validation of the sensor and the development of the analytical system are based on tests carried out in road conditions and in a closed area. Graphical methods (box-plot charts), correlation analysis and testing statistical hypotheses using the Mann–Whitney method were used in the analysis of the test results. The developed sensor and the analytical system allow for identifying the driving style of drivers. This system, through the use of a sensor that allows for downloading data not only from the car’s CAN bus but also the forces acting on the vehicle, permits the checking of 14 driving parameters used to interpret the driver’s driving style.

Open World Intrusion Detection: An Open Set Recognition Method for CAN Bus in Intelligent Connected Vehicles

Open World Intrusion Detection: An Open Set Recognition Method for CAN Bus in Intelligent Connected Vehicles

喷杆倾角控制系统的设计与实验

During field operations of the spray boom sprayer, the distance between the ends of the spray boom and the height of the crop canopy affects the uniformity of spraying, requiring operators to manually adjust the spray boom to be parallel to the crop canopy, which impacts operational efficiency. This study presents the design of a boom tilt control system, consisting of a main control node, distance measurement node, vehicle tilt detection node, and spray boom tilt control node. The bus communication protocol for the spray boom tilt control system is defined according to the ISO11783 standard, and a serial communication network is designed, along with the development of a real-time dynamic monitoring interface for the spray boom. The system automatically monitors the height of the boom and the tilt of the vehicle, makes decisions based on the detection information, controls the electric actuator, and adjusts the tilt of the boom. Leveraging the advantages of fast computing speed and user-friendly human-machine interface of the PC, as well as the high cost-effectiveness and small size of the microcontroller, and the multi-master-slave structure of the CAN bus, this system can complete data acquisition, processing, and other functions required for spray boom tilt control, achieving automatic adjustment of spray boom tilt. This enhances spray uniformity and operational efficiency of the sprayer, while reducing the workload of operators.

IoVCipher: A low-latency lightweight block cipher for internet of vehicles

The data security of CAN bus system is receiving increasing attention with the rapid development of Internet of Vehicles (IoV). However, traditional ciphers are not the best choice due to the limitations of computation, real-time, and resources of Electronic Control Units in vehicles. Thus, this paper proposes a lightweight block cipher IoVCipher to protect the security of IoV. It is designed focus on the latency and area in round-based architectures (both encryption and decryption) to meet this resource-constrained environments. For this purpose, two S-boxes with low latency and tiny area are constructed in this paper, one involution and one non-involution. Considering the decryption latency, a low latency subkey generation method is designed. In addition, this paper proposes a new extended MISTY structure that makes the encryption and decryption of hardware implementations similar. In comparison to other low-latency lightweight block ciphers such as PRINCE, QARMA, MANTIS and LLLWBC, IoVCipher achieves an effective balance between latency and area in the round-based architecture, and IoVCipher has low latency, low area, and low energy in the fully unrolled architecture. Finally, IoVCipher is implemented on a real-time speed acquisition and encryption testbed to simulate encrypted transmission of real-time speed in a CAN bus environment.

Blockchain integration for in-vehicle CAN bus intrusion detection systems with ISO/SAE 21434 compliant reporting.

The development of Intrusion Detection Systems (IDS) for in-vehicle buses has gained a lot of momentum in recent years as the number of reported vulnerabilities and the degree of interconnectivity for modern vehicles are on the rise. Since intrusion detection is resource consuming, it can be performed on computationally capable Android head units that are now present inside vehicles. Moreover, these units are connected to the internet, which enables the use of more complex algorithms that run in cloud environments. In this work we develop one such approach: an IDS that consists of a locally installed copy, running on head units, and a centralized instance of it that runs in the cloud and monitors traffic for groups of similar vehicles. Additionally, the centralized instance is part of a cloud service for intrusion detection which is continuously updated with the most recent types of attacks. The classification results of the cloud-based service are further analyzed by an incident response team which confirms the presence of known attacks, analyzes new types of attacks and assesses their impact. The output of this activity is stored on the Blockchain as ISO/SAE 21434 compliant reports, ensuring the transparency and traceability of the reported incidents.

Event‐triggered adaptive secure lateral stabilization for autonomous vehicles under actuator attacks

SummaryFalse data injection attacks can disrupt the steering control actions and make a real threat to both the security and safety of autonomous vehicles. In this paper, a secure event‐triggered lateral control approach of autonomous vehicles subject to actuator attacks is investigated. Firstly, an arbitrary unknown actuator attacks is considered in the secure lateral steering control of autonomous vehicles. Thus, to save communication resources for the limited bandwidth CAN bus, the periodic event‐triggered transmission scheme is utilized, transforming the established lateral steering control into a time‐delay system through the consideration of periodic event‐triggered sampling. Then, an adaptive control compensation scheme is developed to mitigate the malicious effects caused by actuator attacks. The proposed secure control approach is skilled in compensating the unknown attacked steering control actions in an adaptive way. The stabilization criteria under the adaptive secure control law is well derived by Lyapunov–Krasovskii method and some linear inequality matrices operations. At last, the effectiveness of the proposed secure control scheme is verified by some numerical experiments borrowed from a practical vehicle.

Low-Cost Throttle-by-Wire-System Architecture for Two-Wheeler Vehicles

<div>This article investigates the performance of a low-cost throttle-by-wire-system (TbWS) for two-wheeler applications. Mopeds/scooters are still restricted as environmentally harmful. TbWSs can contribute to environmental protection by replacing conventional restrictors. Its consisting of an anisotropic magnetoresistance (AMR) throttle position sensor and a position-controlled stepper motor-driven throttle valve actuator. The decentralized throttle position sensor is operating contactless and acquires redundant data. Throttle valve actuation is realized through a position-controlled stepper motor, sensing its position feedback by Hall effect. Using a PI controller, the stepper motor position is precisely set. Both units transmit and receive data by a CAN bus. Furthermore, fail-safe functions, plausibility checks, calibration algorithms, and energy-saving modes have been implemented. Both modules have been evaluated through hardware-in-the-loop testing in terms of reliability and measuring/positioning performance before the system was integrated into a <i>Peugeot Kisbee 50 4T</i> (Euro 5/injected). Finally, the sensor unit comes with a measurement deviation of less than 0.16%, whereas the actuator unit can approach throttle valve positions with a deviation of less than 0.37%. The actuators’ settling time does not exceed 0.13 s in the case of stable, step loss free, and noiseless operation.</div>

Intrusion detection and defence for CAN bus through frequency anomaly analysis and arbitration mechanism

AbstractAs automobile intelligence continues to develop, the electronic control units connected to the Controller Area Network (CAN) bus within vehicles face an increasing number of threats from potential attacks originating from the internet. To address this issue, an intrusion detection and defence method is proposed that is capable of detecting illegal messages through the use of frequency anomaly detection, and subsequently disrupting them through utilization of the CAN bus arbitration mechanism. This proposed method offers a simple implementation compared to traditional approaches, while being able to identify suspicious units and neutralize threats in real‐time. Experimental results demonstrate the effectiveness of this approach.