Towards a Lightweight Intrusion Detection Framework for In-Vehicle Networks

With the emergence of networked devices, from the Internet of Things (IoT) nodes and cellular phones to vehicles connected to the Internet, there has been an ever-growing expansion of attack surfaces in the Internet of Vehicles (IoV). In the past decade, there has been a rapid growth in the automotive industry as network-enabled and electronic devices are now integral parts of vehicular ecosystems. These include the development of automobile technologies, namely, Connected and Autonomous Vehicles (CAV) and electric vehicles. Attacks on IoV may lead to malfunctioning of Electronic Control Unit (ECU), brakes, control steering issues, and door lock issues that can be fatal in CAV. To mitigate these risks, there is need for a lightweight model to identify attacks on vehicular systems. In this article, an efficient model of an Intrusion Detection System (IDS) is developed to detect anomalies in the vehicular system. The dataset used in this study is an In-Vehicle Network (IVN) communication protocol, i.e., Control Area Network (CAN) dataset generated in a real-time environment. The model classifies different types of attacks on vehicles into reconnaissance, Denial of Service (DoS), and fuzzing attacks. Experimentation with performance metrics of accuracy, precision, recall, and F-1 score are compared across a variety of classification models. The results demonstrate that the proposed model outperforms other classification models.

A diesel engine air path model with a WG and an ETV for exhaust temperature controller design and embedded control

In this paper a mean value model of a turbocharged diesel engine air path with an electric wastegate (WG) and an exhaust throttle valve (ETV) is presented. The model is designed with regard to system analysis, controller design, and real-time feasibility. That means, care is taken to ensure that the model contains the relevant dynamics on the one hand and that the requirements for computing power and memory (RAM) are kept as low as possible on the other hand. New approaches for modeling the ETV and the exhaust gas temperature are presented. The latter is formulated via an artificial neural network (ANN) computed outside the model. The ANN is integrated into the model in such a way that the differentiation of the model still provides meaningful results for controller design. Thus, this model may also be used for online computation of nonlinear model predictive controllers (MPC) or nonlinear state observers. The parameters of the model are determined using GT-Power simulation data covering the entire working range of the engine. Only measured variables that are also accessible on the engine test bench are used. All optimization problems to be solved within the parameter determination are presented. It is analyzed which sensors are suitable to support the model in an implementation on an electronic control unit (ECU), and the effect without and with sensor correction is shown in a dynamic test bench measurement. Furthermore, the properties of the generated C code are presented, which are the number of mathematical operations, the runtimes, and the stack size. An evaluation of the real time capability is given based on eigenvalue analyses and the properties of the C code .

Development of a Generic Dual Fuel ECU for Common Rail Diesel Engine Control

<p>Rising costs of diesel fuel has led to an increased interest in dual fuel diesel engine conversion, which can offset diesel consumption though the simultaneous combustion of a secondary gaseous fuel. This system offers benefits both environmentally and financially in an increasingly energy-conscious society. Dual fuel engine conversions have previously been fitted to mechanical injection systems, requiring physical modification of the fuel pump. The aim of this work is to develop a novel electronic dual fuel control system that may be installed on any modern diesel engine using common rail fuel injection with solenoid injector valves, eliminating the need for mechanical modification of the diesel fuel system. The dual fuel electronic control unit developed replaces up to 90 percent of the diesel fuel required with cleaner-burning and cheaper compressed natural gas, providing the same power output with lower greenhouse gas emissions than pure diesel. The dual fuel system developed controls the flow of diesel, gas, air, and engine timing to ensure combustion is optimised to maintain a specific torque at a given speed and demand. During controlled experimental analysis, the dual fuel system exceeded the target substitution rate of 90 precent, with a peak diesel substitution achieved of 97 percent, whilst maintaining the same torque performance of the engine under diesel operation.</p>

Development of a Generic Dual Fuel ECU for Common Rail Diesel Engine Control

<p>Rising costs of diesel fuel has led to an increased interest in dual fuel diesel engine conversion, which can offset diesel consumption though the simultaneous combustion of a secondary gaseous fuel. This system offers benefits both environmentally and financially in an increasingly energy-conscious society. Dual fuel engine conversions have previously been fitted to mechanical injection systems, requiring physical modification of the fuel pump. The aim of this work is to develop a novel electronic dual fuel control system that may be installed on any modern diesel engine using common rail fuel injection with solenoid injector valves, eliminating the need for mechanical modification of the diesel fuel system. The dual fuel electronic control unit developed replaces up to 90 percent of the diesel fuel required with cleaner-burning and cheaper compressed natural gas, providing the same power output with lower greenhouse gas emissions than pure diesel. The dual fuel system developed controls the flow of diesel, gas, air, and engine timing to ensure combustion is optimised to maintain a specific torque at a given speed and demand. During controlled experimental analysis, the dual fuel system exceeded the target substitution rate of 90 precent, with a peak diesel substitution achieved of 97 percent, whilst maintaining the same torque performance of the engine under diesel operation.</p>

(Semi-)Automatically Parsing Private Protocols for In-Vehicle ECU Communications

In-vehicle electronic control unit (ECU) communications generally count on private protocols (defined by the manufacturers) under controller area network (CAN) specifications. Parsing the private protocols for a particular vehicle model would be of great significance in testing the vehicle’s resistance to various attacks, as well as in designing efficient intrusion detection and prevention systems (IDPS) for the vehicle. This paper proposes a suite of methods for parsing ECU private protocols on in-vehicle CAN network. These methods include an algorithm for parsing discrete variables (encoded in a discrete manner, e.g., gear state), an algorithm for parsing continuous variables (encoded in a continuous manner, e.g., vehicle speed), and a parsing method based on upper-layer protocols (e.g., OBD and UDS). Extensive verifications have been performed on five different brands of automobiles (including an electric vehicle) to demonstrate the universality and the correctness of these parsing algorithms. Some parsing tips and experiences are also presented. Our continuous-variables parsing algorithm could run in a semi-automatic manner and the parsing algorithm from upper-layer protocols could execute in a completely automatic manner. One might view the results obtained by our parsing algorithms as an important indicator of penetration testing on in-vehicle CAN network.

Technical vision system for apple defects recognition: justification, development, testing

The most rational method for identifying the quality of fruits is the optical method using PPE, which has the accuracy and stability of measurement, as well as distance and high productivity. The paper presents classification of fruit quality recognition systems and substantiates the design and technological scheme of the vision system for sorting them, consisting of an optical module with installed structural illumination and a video camera, an electronic control unit with an interface and actuators for the sorter and conveyor for fruits. In the course of the study, a single-stream type of fruit flow in PPE with forced rotation was substantiated, a structural and technological scheme of an STZ with a feeding conveyor, an optical module and a control unit, an algorithm for functioning of the STZ software was developed based on algorithm for segmentation of fruit colors, tracking algorithm, etc. deep learning ANN, which provide recognition of the size and color of fruits, as well as damage from mechanical stress, pests and diseases. The developed STZ has been introduced into the processing line for sorting and packing apples, LSP-4 has successfully passed preliminary tests and production tests at OJSC Ostromechevo. In the course of preliminary tests of the LSP-4 line, it was found that it provided fruit recognition with a probability of at least 95%, while the labor productivity made 2.5 t/h.

A design of fuel control unit for eco vehicle engines

Nowadays, solution of fuel injection is the best way for design of fuel economy vehicle while mechanical improvement has almost reached its limit. This article shows result of the research and making the fuel injection electronic control unit (ECU) used for two annually contests named Honda EMC and Shell ECO-marathon. The control circuit is designed and coded with Arduino Mega, sensors and actuators equipped in popular cars. The circuit also allows users to change the fuel injection map and the ignition timing map to suit ECO vehicle, its necessary data help driver to have better seeing and adjusting during contest time. This permit contestant teams to modify base on their design and showed data can help contest process become more optimized and simply.

An Experimental Study on a Dual-Fuel Generator Fueled With Diesel and Simulated Biogas

Diesel fueled generators are widely used for power generation in remote and/or off-grid communities. In such communities, local organic waste streams can be used to generate biogas which can be used to replace diesel used by diesel generators to lower fuel cost and reduce greenhouse gas (GHG) emissions. Diesel powered generators can be easily retrofitted with a biogas dosing line in the engine intake to introduce biogas, but appropriate optimization would be of great help to further improve generator performance and reduce GHG emissions. The objective of this research is to demonstrate simplified optimization methods that can reduce GHG emissions (carbon dioxide and methane) from such retrofitted dual-fuel engines under various biogas compositions. The study was conducted on a modern 30 kilowatt (kW) generator using an electronically controlled, four-stroke, four-cylinder, direct injection, turbo-charged diesel engine. The engine was operated with the factory electronic control unit (ECU) and a programmable ECU which allowed for control of the fuel injections and exhaust gas recirculation (EGR) valve. Biogas was simulated by using natural gas (with more than 95% methane by volume) which was diluted with either carbon dioxide or nitrogen. This study consisted of two areas. The first one was the comparison of the engine performance when operating with biogas using the factory ECU and the programmable ECU with user optimized fuel injection. The second one was the influence of volume fraction of carbon dioxide or nitrogen in the biogas. The test results reinforced the importance of optimizing the diesel injections when the engine was operated in the biogas-diesel dual-fuel mode to ensure complete combustion and achieve a reduction in GHG emissions. Increasing nitrogen fraction had a minimal effect on the emissions, but increasing carbon dioxide fraction caused the NOx and methane emissions to decrease, and the indicated thermal efficiency to increase.

Comparative Analysis of Performance, Emission, and Combustion Characteristics of a Common Rail Direct Injection Diesel Engine Powered with Three Different Biodiesel Blends

Biodiesel is a renewable energy source which is gaining prominence as an alternative fuel over fossil diesel for different applications. Due to their higher viscosity and lower volatility, biodiesels are blended with diesel in various proportions. B20 blends are viable and sustainable solutions in diesel engines with acceptable engine performance as they can replace 20% fossil fuel usage. Biodiesel blends are slightly viscous as compared with diesel and can be used in common rail direct injection (CRDI) engines which provide high pressure injection using an electronic control unit (ECU) with fuel flexibility. In view of this, B20 blends of three biodiesels derived from cashew nutshell (CHNOB (B20)), jackfruit seed (JACKSOB (B20)), and Jamun seed (JAMNSOB (B20)) oils are used in a modified single-cylinder high-pressure-assisted CRDI diesel engine. At a BP of 5.2 kW, for JAMNSOB (B20) operation, BTE, NOx, and PP increased 4.04%, 0.56%, and 5.4%, respectively, and smoke, HC, CO, ID, and CD decreased 5.12%, 6.25%, 2.75%, 5.15%, and 6.25%, respectively, as compared with jackfruit B20 operation.