CAN Bus System Research Articles

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.

Physiological and Behavioral Changes of Passive Fatigue on Drivers during On-Road Driving

Driver fatigue can be further categorized into passive fatigue and active fatigue based on the task-induced fatigue perspective, with its categorization necessary from a theoretical basis and practical needs. Passive fatigue is caused by mental underload and inactive task engagement, which is considered more hazardous. To facilitate the construction of the driver monitoring system (DMS), the current study aims to investigate the physiological and behavioral changes of passive fatigue. A total of thirty-six participants completed a 90 min driving task on a monotonous highway, during which subjective fatigue level, eye tracking indicators, and driving dynamics were recorded using the Stanford Sleepiness Scale, Smart Eye Pro, and CAN Bus system. Results showed that drivers reported higher levels of fatigue as driving duration increased. An increase in pupil diameters and gaze dispersions were observed during the task. Drivers gradually reduced the control of the vehicle, in which faster speed and lower speed compliance were witnessed. In addition, a compensatory process was found as passive fatigue increased. Drivers tended to lower their standards to maintain the lateral position but recovered their lateral control when they lost control of the car speed. The current study emphasizes the importance of investigating active and passive fatigue of drivers independently, and the unique physiological and behavioral changes accompanied by passive fatigue should be considered in designing driver monitoring systems.

Virtual CANBUS and Ethernet Switching in Future Smart Cars Using Hybrid Architecture

Smart cars have gained much attention in recent years due to the introduction of several safety and convenience features. In this paper, we propose a virtual CANBUS architecture that will improve the safety and data processing in future smart cars with the hybrid use of Ethernet technology deployed in conjunction with a CANBUS system to take advantage of the virtualization, speed, and quality of data processing. Data will be routed intelligently across the dual data paths of the traditional CANBUS and the Ethernet. The virtualized nature, with the help of a series of smart nodes and network traffic analyzers, will allocate the needed resources at the right time during the execution of different processes. This enables the possibility of routing data traffic over both Ethernet and CANBUS connections. The architecture is backward compatible with older vehicles and therefore takes advantage of the existing CANBUS system. The proposed architecture ensures that different segments are isolated from each other so that a breakdown in a segment does not bring down the entire system. The experimental results demonstrate the benefits of the proposed solution, which is to switch between two data pathways depending on the traffic loads. While the CANBUS is sufficient with low-bandwidth data, the Ethernet will create a better performance with high-bandwidth processes. The virtualized environment creates virtual topologies among communicating nodes, greatly simplifying the network management and enhancing the data traffic performance as the bandwidth requirement and the number of processors in future smart cars continue to scale.

Damage Diagnosis of Cardan Shafts in Mobile Mining Machines using Vibration Analysis

The ability of prediction of machine condition may become even more crucial in mobile mining machines considering their instantly-varying conditions. The field of early damage diagnosis for mobile machinery is gaining increasing attention in modern and predictive maintenance strategies. In general, vibration-based machine condition monitoring methods offer the possibility to detect and localize the damages in mechanical systems at their early stages. In vibration monitoring, the vibration signals are captured via accelerometers, and are processed in the time and frequency domains in signal processing packages to extract diagnostic information. However, in real-world mobile applications, vibration analysis alone may not reveal the diagnostic information due to extreme transient and nonstationary operating conditions. In this regard, additional metadata available on the machine’s CAN bus system, can improve the reliability of vibration analysis for mobile applications. The current study aims to investigate the usage of metadata as additional information to the vibration analysis on cardan shaft of a test wheel loader in field conditions. Two various damage types, namely, misalignment and bearing clearance, both on cardan shaft, are investigated in some detail. The experimental results show how vibration analysis together with metadata processing can identify the state of the machine even in harsh operating conditions.

Reliability Sensitivity Analysis of Vehicle CAN Bus Message Transmission Based on Second-moment Method

CAN bus, as one of the most successful on-board network systems, is widely used in modern automobiles. The main function of CAN bus is to realize timely and accurate message transmission, so higher and higher requirements are put forward for the reliability of message transmission. In this paper, a typical CAN bus message transmission model was selected for analysis, and the reliability sensitivity of the bus message transmission was analyzed and calculated based on the reliability second-moment theory. The results were consistent with the qualitative analysis, and the reliability sensitivity calculation of the second-moment method is verified. The reliability sensitivity analysis of CAN bus message transmission by this method will provide a reasonable theoretical support for the further study of message transmission reliability in CAN bus system.

Driver Profiling Using Long Short Term Memory (LSTM) and Convolutional Neural Network (CNN) Methods

Driver profiling has a major impact on traffic safety, fuel consumption and gas emission. LSTM and CNN based neural network models were developed to classify and assess bus driver behavior characterized by deceleration, engine speed pedaling, corner turn and lane change attempts. Deceleration, engine speed and corner turn test scenarios were performed on concrete paved test track while lane changing tests were conducted on a commercial asphalt highway. Despite the majority of studies relying on image, vehicle data and additional sensor fusion, here only the data streams received from vehicle CAN Bus system were used to train the proposed network architectures. After parsing the data into meaningful characteristic parameters, different LSTM and CNN architectures were trained by varying the number of layers, neurons and epoch number. Both LSTM and 1D-CNN networks resulted in comparable success rates. CNN architecture indicates better performance indices for identification of aggressive driving compared to LSTM network for behavioral modelling.

CAN BUS BASED BMS CONTROL CARD DESIGN AND IMPLEMENTATION BY USING STM32f103 SERIES MICROCONTROLLER

In this study, battery charge control circuit design which is used for storage in electric vehicles or renewable energy system has been realized. The BMS card is designed for a system of four battery cells. The circuit board is designed based on the CAN-Bus communication system and the STM32f103 series microprocessor is used. Circuit design is made of industrial circuit board specifications. Battery Management System (BMS) card design was realized by taking into consideration the methods to reduce the electromagnetic noise. In this study CAN-Bus communication protocol especially selected. Thanks to this protocol, data from many sensors in the vehicle can be controlled using only 2 wires. Although CAN protocol is used mainly in automotive sector, it is used in many systems including microprocessor due to the reasons such as data transmission rate, low error rate and ease of application. The power circuit, control units and CAN Bus communication layer of the designed card have been tested and ready for use.

Research on Construction of Crude Set Model of Critical Fault Information for Bus Based on CAN-BUS Data

Under the high load, high frequency and high strength operating environment, the frequent occurrence of vehicle fault gradually attracts the attention of the society. The real-time monitoring and data recording function of vehicle-mounted equipment provides data support for vehicle status assessment and fault warning. In this paper, the real-time data collected by CAN-BUS system of Beijing Bus Group are preprocessed and discretized. On the basis of the traditional rough set theory, a new coding method is set up, and the dependency between conditional attributes and decision attributes is set as an adaptive function, which is reduced by genetic algorithm and cellular genetic algorithm respectively. The calculation results show that the key fault information of public transport vehicles is instrumental speed, oil pressure, percentage of torque, timing engine speed, and coolant temperature. By comparing the results of reduction, it is found that the cellular genetic algorithm has higher applicability than the genetic algorithm in terms of algorithm efficiency, stability, and convergence quality. Although the genetic algorithm attribute reduction is slightly better than the cellular genetic algorithm attribute reduction in the rule matching, the cellular genetic algorithm has a better ability to excavate information within the acceptable compatibility range. Finally, the selected key factors will be deployed on the Beijing Bus Group's big data platform and displayed in real time. The conclusion of this paper enriches the theory of bus engine fault warning and establishes an engine failure warning system, which can effectively reduce the failure rate of bus vehicles and reduce the maintenance cost expenditure. It has certain guiding significance for the bus operation work of Beijing Bus Group.

Statistical Analysis of Improved Bit-stuffing Method Based on CAN Bus

The stuffing bit of the CAN bus is closely related to the transmission performance of the bus system. Therefore, it is very important to reduce the stuffing bit to improve the performance of the bus. In this paper the stuffing mechanism of CAN bus was analyzed, and the XOR stuffing method proposed by previous researchers was drew on, then the necessary correction was made to improve the XOR stuffing method to reduce the stuffing bit more reasonably. Through the modeling and analysis about the improved XOR method, it is found that the stuffing bit based on improved XOR stuffing method is a random variable, and the probability distribution maps of stuffing bit were obtained through programming simulation. Combined with the simulation probability distribution curves and related formulas, we deduced the statistical characteristics of the stuffing bit with the improved XOR stuffing method, which will provide a reasonable theoretical basis for further research and analysis of CAN bus system.

CAN COMMUNICATION MODEL TO HANDLE VEHICLE CONTROL SYSTEM & ITS APPLICATIONS USING RASPBERRY PI

CAN communications helps us to engrave the complex wired source into the simple form. Using raspberry pi CAN bussystem can work effectively to access the vehicle internal ECU parameters and now-a-days different applications withIOT compliance. We can control the vehicle system remotely using the raspberry pi application. Also, not only for the system of vehicle we can control the home equipment’s using this technique. So automation which is the need of future can be effectively managed using the CAN withIOT convergence. We suggest some basic implementation of such scenarios over this paper.

Open source implementation of ECSS CAN bus protocol for CubeSats

With the ever growing capabilities of space-grade FPGAs and microcontrollers, spacecraft systems are evolving from centralized architectures with a single main processing unit to decentralized layouts composed of multiple intelligent nodes. The backbone of this development is the command and control bus that interconnects these units. Used in terrestrial applications since decades, the CAN bus provides performance and robustness similar to other more traditional spacecraft buses such as MIL-STD-1553, but at very low cost. The European Cooperation for Space Standardization has published a standard in mid 2015 that specifies the requirements for a CAN bus system for space application. In this paper we present the details and results of a prototype implementation of this standard for CubeSat missions. We demonstrate that the minimal implementation of this protocol stack can well be adapted to the tight constraints of microcontrollers. The main advantages of this standardized CAN bus are increased reliability and higher data throughput, as compared to other commonly employed bus systems on CubeSats.

The impact of road geometry, surface roughness and truck weight on operating speed of logging trucks

ABSTRACTImproved transport planning and pricing is dependent on correct cycle times. The objective of this study was to quantify the effect of road curvature, surface roughness, gradient and truck weight on the operating speed of a conventional 60-tonne gross vehicle weight logging truck. The study used a 320-km test track consisting of both public and forest roads. The track was driven with various gross vehicle weights. Speed data was retrieved from the truck’s CAN-bus system and road data was measured with a profilograph. The key factors for operating speed were curvature and surface roughness, both of which were correlated to each other as well as partially captured by functional road class. Regression analysis quantified the individual effects of these factors as well as gradient, undulation and interactions with truck weight. A regression model is presented which explained 80% of the variation in operating speed. The results were consistent with previous studies, and the proposed models can be used to improve transport planning, cost estimation, operative route path selection and road investments.

The impact of road geometry and surface roughness on fuel consumption of logging trucks

ABSTRACTFuel accounts for more than 35% of transport costs in Swedish forestry, and reduced fuel consumption would provide immediate economic and environmental benefits. The objective of this study was to quantify the effect of road gradient, curvature and surface roughness on fuel consumption of a conventional 60-ton logging truck. The study used a 320-km test track on both public and forest roads. The track was driven with various load weights in both dry summer and wet autumn conditions. Fuel consumption data were retrieved from the truck's CAN-bus system, and road data were measured with a profilograph. Average fuel consumption was 71.4 litres/100 km. A regression analysis showed that the most important factor was the interaction between vehicle weight and gradient, explaining the 86% increase between empty and fully loaded truck. In addition, the regression analysis quantified the individual effects of undulation, curvature and surface roughness, explaining the 107% increase in fuel consumption between the highest and lowest road class. Results from the proposed regression model (R2 of 84% for a road section length of 1000 m) were consistent with predictions given by the European ARTEMIS model, and the proposed model can be used to improve cost estimation and route selection.

Period Optimization Scheduling Algorithm Research of CAN Bus in Electric Vehicle

Improving the real-time performance of CAN bus is the focus problem of in-vehicle network design. It can improve the efficiency of message transmission to meet the needs of system control requirement. This paper firstly put forward the message response time calculation method of CAN bus considering a periodic correction coefficient. Secondly, based on the message response time calculation method using periodic correction coefficient, the periodic scheduling algorithm was designed and researched, using nonlinear programming method. The efficiency of periodic scheduling algorithm was validated by an optimization example of hybrid electric vehicle message set. It can be used in the CAN bus optimization design stage, and as a guidance for the CAN bus system design.

TTCAN在ARM中的应用实现

CAN总线是现场总线的一种，目前在汽车电子和船舶电子中广泛应用。针对CAN通信网络中低优先级数据传输延迟较大、存在稳定性较差的问题，提出了基于时间触发的TTCAN协议。本基于时间触发的双路CAN总线系统是由ARM工控机控制，是具有一个主节点和n个从节点的系统，并在后续作出错误率检测与现有的总线结构作比较以证明该总线结构的可行性。 CAN bus is a kind of field bus and is widely used in automotive electronics and marine electronics. For the data transmission delay of low priority number is large and the stability is poor in CAN communication network, time-triggered TTCAN protocol is proposed in this paper. The time- triggered dual CAN bus system is controlled by ARM IPC, which consists of one master node and several slave nodes. This system is compared with the existing CAN bus system on the subsequent error rate to demostrate the feasibility of this system.

A neural network approach for indirectly estimating farm tractors engine performances

The instant torque and brake specific fuel consumption (BSFC) of a farm-tractor engine are very interesting parameters from a technical and economical point of view and allow advancing many considerations in the Engineering and Farm-mechanization fields related to the optimization of the engine power and consumptions. A direct access to the CAN-BUS system, where present, can be difficult; as a consequence, some practical solutions (sensors, numerical methodologies) aimed to deduce continuously but indirectly the engine performances are therefore proposed and discussed.In particular, the focus of this study is to evaluate the possibility of using artificial neural networks (ANNs) trained with exhaust gas (EG) and motor oil temperature data, easy to be measured. Hence, the above-mentioned temperatures and several network architectures (different for neurons and hidden layers number, neuronal transfer functions) were evaluated in their reliability in estimating the torque and BSFC of different tractor diesel motors, giving also the readers some useful indications: determination coefficients were calculated with reference to the line “predicted values=experimental values”.Lubricant temperature resulted to be totally unsuitable (very low and diversified R2).ANNs using the EG temperature for torque estimations achieved higher average R2 than ANNs predicting BSFC, both in the training (>0.996 vs. >0.889) and in the prediction phase (>0.993 vs. >0.621). Consequently, EG temperature is strongly recommended for estimating both parameters even if preliminary evaluations should be performed for BSFC (engine characteristics have a significant influence on the predictions).Finally, best R2 can be scored by using the Gaussian neuronal transfer function.

Design and Implementation of Campus Card in Shower System

s: This paper analyzes the application characteristics of campus smart card and electronic account, from the students requirements of shower management, made some research and Study on the campus smart card electronic account application and the CAN bus data transmission and developed a general admission fee based on network of campus card and CAN bus communication system, realize no cash operation in the finance charge project. This paper is discussed in detail from the communications and design payment system, interface, security aspects, and provides a reference of smart card application for the similar colleges.

The Stability Analysis Based on EDF Scheduling Algorithm in CAN Bus

The CAN bus scheduling performance can be very important for the design of CAN bus system, it is related to the normal operation of the bus system. The CAN bus scheduling performance is studied and calculated using the classical first order second moment method based on EDF scheduling method; an example of the bus system scheduled by EDF method is used to calculate the stability by this method. MONTE-CARLO simulation is imitated using software programming; by comparing the results above the formula proves correct.

The Stability Studies of the Message Transmission in CAN Bus

The message transmission stability is very important for the design of the CAN bus system, which is related to the normal operation of the bus control system. The message transmission time is analyzed based on the Tindell scheduling theory, and the message transmission stability analysis is studied by means of probability analysis based on the second-moment method. An example in vehicle is calculated to get its message stability and the result is contrasted with the MONTE-CARLO method, and then the message transmission stability can be got using the method above; this will be the basis for calculating the stability of the CAN bus system, and provides the foundation for the further scheduling theory studies. It has great practical significe for CAN bus.

Development of Tractor Automatic Controlled Boom Sprayer Using CAN-BUS

In Japan, comfort and efficiency are being pursued for sprayer. To respond to this need, tractor automatic controlled boom sprayer using CAN-BUS was prototyped and developed. In this paper, the configuration and function of the boom sprayer equipped with CAN-BUS are described. In addition, the sprayer performance test is discussed. The CAN-BUS system of the boom sprayer, plugged tractor ECU, is comprised of two sprayer ECUs and two controllers. In order to respond to changes in the target spray volume per unit area, the sprayer sends the target tractor speed to the tractor by CAN-BUS and the tractor adjusts its traveling speed accordingly. The performance test of boom sprayer confirmed that the precision of application rate achieved by this system is high enough for practical use.