On-board Diagnostic System Research Articles

Clarifying the impact of engine operating parameters of heavy-duty diesel vehicles on NOx and CO2 emissions using multimodal fusion methods

The issue of air pollution from transportation sources remains a major concern, particularly the emissions from heavy-duty diesel vehicles, which pose serious threats to ecosystems and human health. China VI emission standards mandate On-Board Diagnostics (OBD) systems in heavy-duty diesel vehicles for real-time data transmission, yet the current data quality, especially concerning crucial parameters like NOx output, remains inadequate for effective regulation. To address this, a novel approach integrating Multimodal Feature Fusion with Particle Swarm Optimization (OBD-PSOMFF) is proposed. This network employs Long Short-Term Memory (LSTM) networks to extract features from OBD indicators, capturing temporal dependencies. PSO optimizes feature weights, enhancing prediction accuracy. Testing on 23 heavy-duty vehicles demonstrates significant improvements in predicting NOx and CO2 mass emission rates, with mean squared errors reduced by 65.205 % and 70.936 % respectively compared to basic LSTM models. This innovative multimodal fusion method offers a robust framework for emission prediction, crucial for effective vehicle emission regulation and environmental preservation.

The CornerGuard: Seeing around Corners to Prevent Broadside Collisions

Nearly 3700 people are killed in broadside collisions in the U.S. every year. To reduce broadside collisions, we created and tested the CornerGuard, a prototype system that senses around a corner to alert a car driver of an impending collision with a pedestrian or automobile that is not in the line of sight (LOS). The CornerGuard leverages a microwave-transceiving radar sensor mounted on the car and a curved radio wave reflector installed at the corner to sense around the corner and detect a broadside collision threat. The car’s speed is constantly read by an onboard diagnostics (OBD) system to allow the sensor to differentiate between static objects and objects approaching around the corner. Field testing demonstrated that the CornerGuard can effectively and consistently detect threats at a consistent range without blind spots under broad weather conditions. Our proof of concept study shows that the CornerGuard can be enhanced to be readily integrated into automobile construction and street infrastructure.

Recent Advances in SCR Systems of Heavy-Duty Diesel Vehicles—Low-Temperature NOx Reduction Technology and Combination of SCR with Remote OBD

Heavy-duty diesel vehicles are a significant source of nitrogen oxides (NOx) in the atmosphere. The Selective Catalytic Reduction (SCR) system is a primary aftertreatment device for reducing NOx emissions from heavy-duty diesel vehicles. With increasingly stringent NOx emission regulations for heavy-duty vehicles in major countries, there is a growing focus on reducing NOx emissions under low exhaust temperature conditions, as well as monitoring the conversion efficiency of the SCR system over its entire lifecycle. By reviewing relevant literature mainly from the past five years, this paper reviews the development trends and related research results of SCR technology, focusing on two main aspects: low-temperature NOx reduction technology and the combination of SCR systems with remote On-Board Diagnostics (OBD). Regarding low-temperature NOx reduction technology, the results of the review indicate that the combination of multiple catalytic shows potential for achieving high conversion efficiency across a wide temperature range; advanced SCR system arrangement can accelerate the increase in exhaust temperature within the SCR system; solid ammonium and gaseous reductants can effectively address the issue of urea not being able to be injected under low-temperature exhaust conditions. As for the combination of SCR systems with remote OBD, remote OBD can accurately assess NOx emissions from heavy-duty vehicles, but it needs algorithms to correct data and match the emission testing process required by regulations. Remote OBD systems are crucial for detecting SCR tampering, but algorithms must be developed to balance accuracy with computational efficiency. This review provides updated information on the current research status and development directions in SCR technologies, offering valuable insights for future research into advanced SCR systems.

Analysis of security vulnerabilities in vehicle On-Board Diagnostic systems

Analysis of security vulnerabilities in vehicle On-Board Diagnostic systems

Automotive digital forensics through data and log analysis of vehicle diagnosis Android apps

Modern vehicles including smart cars have been equipped with many electronic devices such as electronic control units (ECUs), on-board diagnostics (OBD) systems, telematics and infotainment systems, gateways, sensors, etc. Because these devices create, transmit, and store a lot of digital data, modern vehicles are becoming key source of digital evidence in vehicular forensics. In addition, some dedicated mobile apps can capture driving and diagnostic data from a vehicle via a Bluetooth-enabled OBD-II scanner. In this paper, we propose a new process for effective automotive forensics. It collects and analyzes three different types of data left on an Android phone which has been connected to the OBD-II port of a vehicle via Bluetooth communication. The three types of data are OBD-II Android apps' data, Bluetooth HCI snoop log, and the main log buffer of the Android logging system. By analyzing them individually and integratedly, we find Bluetooth connection time, vehicle information, MAC address of the OBD-II scanner, vehicle velocity, sharp speeding event, sudden braking event, refueling event, and so on. We also construct a timeline of Bluetooth traffic and driving events through the timeline analysis, which can be used to determine the driver's behaviors in terms of vehicle forensics.

Synthesis of the structural diagram with algorithms of the units of the on-board diagnostic system of induction motors of vehicles

Synthesis of the structural diagram with algorithms of the units of the on-board diagnostic system of induction motors of vehicles

Developing Fuel Efficiency and CO2 Emission Maps of a Vehicle Engine Based on the On-Board Diagnostic (OBD) Approach

A vehicle interacts with the road, other vehicles, and traffic control devices in real traffic conditions. The level of traffic influences driving patterns and, consequently, this can affect the vehicle´s fuel efficiency and emissions. This study aims to develop engine maps of fuel consumption and CO2 emissions for a light vehicle operating under real traffic conditions. A representative passenger vehicle of the Ecuadorian vehicle fleet, powered by gasoline, was selected for the experimental campaign that was developed on a test route designed according to real driving emission (RDE) regulation. An on-board diagnostic (OBD) device was used for recording in real-time engine and vehicle operating parameters. Moreover, CO2 emissions were estimated using the fuel rate registered from the OBD system of the vehicle This study proposed a novel methodology for developing two-dimensional contour engine maps based on OBD data. The result showed that the vehicle engine operated in real traffic conditions with a brake thermal efficiency (BTE) of 27%, a brake-specific fuel consumption (BSFC) of 275 g/kWh, and a carbon dioxide (CO2) energy-emission factor of 716 g/kWh. In terms of distance, the CO2 emission factor for the tested vehicle was approximately 190 g/km. Overall, this study demonstrates that the OBD approach is a potential method to be used to assess the fuel consumption and emissions of a vehicle operating under real-world traffic conditions, especially in Latin American countries, where portable emission measurement systems (PEMS) are not readily available.

Diagnostics of inter-turn short circuits in phase stator windings of permanent magnet synchronous machines

BACKGROUND: Currently, electric buses are becoming more widespread in the segment of urban passenger transportation due to the absence of harmful emissions and low noise levels. Permanent magnet synchronous machines (PMSM) are widely used as a traction motor.
 One of the most promising methods of monitoring the technical condition of traction motors is diagnostics using monitoring tools installed on board of a vehicle. The advantages of such methods include the possibility of regular frequent condition checks (as opposed to much rarer diagnostics in stationary maintenance points) and a more rapid response to the development of identified malfunctions, which significantly reduces the cost of maintenance and repair of expensive equipment. The disadvantages include limitations associated with a shortage of layout space for the placement of diagnostic equipment, with the limited capabilities of on-board computer facilities for the transmission and storage of diagnostic information and with the complexity of computational procedures of built-in expert diagnostic systems.
 Concerning the types of operational failures of PMSMs, which are the most common and the most severe in terms of the cost of restoring operability, these are inter-turn short circuits in the stator windings, increased eccentricity of the air gap between the stator and the rotor, bearing damage, as well as damage of the mechanical gearbox coupled with the electric motor.
 AIM: Identification the diagnostic signs of inter-turn short circuits in the phase windings of a permanent magnet synchronous machine, helping to detect these malfunctions on board of route urban vehicles at an early stage.
 METHODS: A mathematical model of a permanent magnet synchronous machine with short-circuited turns of the phase winding, which makes it possible to study the behavior of the motor with a various number of short-circuited turns, has been developed.
 RESULTS: For the first time, the requirements for diagnostic features for the on-board diagnostic system of an urban electric bus, making it possible to detect inter-turn short circuits in the phase windings of traction electric motors at the early stages of the origin of a malfunction, are formulated.
 The main parameters of the process of digital registration of phase currents have been obtained, helping to do measurements and to transmit signals through the onboard information network of the electric bus.
 Using simulation modeling methods, it was found that the peak values of the linear spectrum of the total current vector are stable diagnostic signs that make it possible to detect inter-turn short circuits in the phase windings of traction motors at the early stages of the origin of the malfunction.
 CONCLUSION: The practical value of the study lies in the opportunity of using the proposed methods for diagnosing the technical condition of traction electric drive units in urban passenger electric transport.

Measurement of engine performance and maps-based emission prediction of agricultural tractors under actual operating conditions

This paper develops a comprehensive data collection system (CDCS) based on radio frequency identification (RFID) technology, on-board diagnostic system (OBD), and portable emission measurement system (PEMS) to study the performance of tractors in the real world. The actual operating modes, fuel consumption and emission levels of the tractor engine were studied and the braking thermal efficiency (BTE) under actual operating conditions was reported for the first time, with a maximum value close to 45%. The engine maps were developed and used to predict tractor emissions and fuel consumption, and the results showed that it can accurately predict tractor fuel consumption and carbon dioxide (CO2) emissions, with mean absolute percentage error (MAPE) and coefficient of determination (R2) values reaching over 90%. This article provides a reliable testing and prediction method for the actual performance of tractor engines, and suggests that real performance indicators should be given better attention.

Research on and Assessment of the Reliability of Railway Transport Systems with Induction Motors

Increasing the efficiency and reliability of modern railway transport is accompanied by an increase in monitoring and diagnostic systems for the current state of electric drives. Modern railway transport contains a large number of induction motors to ensure the operation of the drives of various mechanisms. In the article, based on the operational statistics of engine failures and the proposed scheme for diagnosing them, studies were carried out and a model was developed for assessing the reliability of a transport system equipped with an on-board diagnostic system for the current state. When building the models, the Markov method was used, including the construction of graphs for the five most relevant states of the induction electric motor during operation. The results obtained are relevant for evaluating the effectiveness of using the built-in diagnostic system and scheduling routine maintenance, which will affect the efficiency of railway transport. Based on the process of the diagnosis of railway transport systems with induction motors, five operating states of the object studied were interpreted: the state of full operation, state “S0”; the state of incomplete serviceability, state “S1”; critical serviceability, state “S2”; the state of the pre-damage condition, state “S3”; the state of unserviceability (defect), state “S4”. Subsequently, a five-state model of the operation process of railway transport systems with induction motors was developed. This model is also described by equations of state: Kolmogorov–Chapman equations. The reliability quantities determined form the basis for simulation reliability studies. The effect of the simulation study is the reliability quantities determined in the form of reliability functions and probabilities of the occurrences of the operating states of railway transport systems with induction motors; an important part of the reliability study of the system examined is to estimate the times of the occurrences in the object studied of the operating states in the future.

On-board system for diagnosing the cooling system of cars

The complexity of diagnosing the cooling system is determined by many reasons. First, the efficiency of the cooling system in operation depends on both the technical and operational characteristics and the state of the engine. Secondly, reliable instrumental means of monitoring the technical state of the elements of the cooling system in operation are still virtually absent. For effective operation it is necessary to pay attention to the technical condition of the cooling system, because its malfunction can lead to the downtime of the car. With the help of the proposed survey part of the on-board diagnostic system, it is possible to detect malfunctions of the cooling system elements. Keywords: On-board diagnostic system, car, cooling system, sensor, temperature

A real-time NOx emission inventory from heavy-duty vehicles based on on-board diagnostics big data with acceptable quality in China

With the phase-in of China VI emission standard for heavy-duty vehicle (HDV), increasing numbers of HDVs are mandatorily equipped with on-board diagnostic (OBD) systems, providing opportunity to remote monitoring and supervision of emissions from in-use vehicles. However, the quality problem of OBD data is serious and lack of comprehensive assessment. In this study, the quality of nearly 1.6 billion OBD data from 38,692 China VI diesel HDVs travelling inside the Tangshan city of China was evaluated using a proposed framework which consists of validity indicators and signal transmission indicators. More than 24% of vehicles had overall invalidity rate over 20%, and only 0.4% of vehicles met the transmission period requirement of 1 Hz, indicating that the necessity and urgency for supervising and improving the OBD data quality. In particularly, several specific vehicle models were more prone to data quality problems, especially in the inability to determine the emission-related information. A real-time street-level NOx emission inventory was developed based on the OBD data with acceptable quality, using the direct monitoring and calculation of instantaneous emissions from each HDV. Compared to those from the top-down method which relied on gridded emissions and spatial allocation proxy schemes, the temporal and spatial characteristics of our results reflected the distribution and variations of actual freight demand in the real world. The developed real-world emission inventory will provide accurate support for the policy-making of precise control measures on HDVs.

An Analysis of Emission Exhaust Gas on 4-Stroke Engine Based on IOT Gas Analyzer

According to the Air Quality Live Index (AQLI), Indonesia's air quality has continued to deteriorate in the last two decades, so Indonesia is officially ranked 17th as the country with the worst air quality in the world. This is due to the population explosion in Indonesia causing industrial activity to also increase. The high levels of exhaust emissions in vehicles, of course, requires the need for technology to measure vehicle exhaust gases to reduce the impact of air pollution. However, the procurement of exhaust emission test equipment is still expensive, so only certain class workshops have this tool. In addition, the reading results of the vehicle's OBD (On Board Diagnostic) system are only able to display the condition or reading value of the Lambda sensor because other gas sensors readings such as CO2, HC, and CO cannot be displayed on the OBD reading results. The purpose of this study is to describe the design of the tool and the results of measuring CO and HC levels through the Blynk application. Research methods that use several gas sensors, such as MQ-7 and TGS-2602 (CO gas) and MQ-2 and TGS-2611 (HC gas), are then compared with the measurement results of a standard gas analyzer. The results showed that the MQ-7 value is close to the accuracy at 1000 rpm and 5000 rpm, namely 99.68% and 99.49%, while the level of accuracy at 3000 rpm is 99.37%. The TGS-2602 sensor at 1000 rpm only has the best accuracy and accuracy, namely 99.67% and 99.77%. The level of accuracy of the MQ-2 sensor has the best value at 1000 rpm rotation, which is 95.71% and the level of accuracy has the highest value at 7000 rpm rotation, which is 100%. For the level of accuracy of the TGS-2611 sensor, it has an accuracy level of 1000 rpm rotation of 94.65% and the level of accuracy of the sensor obtains very good values ​​at 1000 rpm, 7000 rpm, and 9000 rpm rotation of 100%.

Prerequisites for the creation of domestic onboard diagnostics tools for the M1 and M2 categories vehicles

BACKGROUND: Due to the steady growth of the worldwide fleet of vehicles alongside the sophistication of their operational functions and the increase in the number and manufacturability of electronic control units, used in a vehicle, the demand for means of access to the performance of on-board electronic sys-tems at the final stages of their production and operation is increasing. This review is necessary to summarize the available data from the world experience in the development and implementation of on-board diagnostic systems.
 AIMS: Formulation of general principles for the development of onboard diagnostic systems, helpful to outline reasonable technical solutions for the task of creation of proprietary domestic diagnostic environment for vehicles.
 METHODS: This paper describes the purpose and role of onboard diagnostic systems used in world practice for modern vehicles. Classes of diagnostic devices are allocated according to the level of implemented functions. The grounds that determine the demand for development of proprietary onboard diagnostic systems for wheeled vehicles are considered. A review of the functionality of the original diagnostic tools of foreign vehicle manufacturers was carried out. The main requirements imposed on developers by the ISO 27145 and ISO 14229 group of standards within the framework of the implementation of modern diagnostic systems in domestic vehicles of the M1 and M2 categories are determined.
 RESULTS: A specific set of functions recommended for integration into diagnostic equipment being developed as a part of promising domestic developments has been determined. The content of the positive effect of the practical implementation of the measures proposed according to the results of the analysis is formulated.
 CONCLUSIONS: The performed scientific analysis of the features of the existing diagnostic equipment is helpful to determine the relevant trends in the implementation of a fundamentally new trend in on-board diagnostics in the Russian Federation, which contributes to increasing the level of competence of domestic specialists and development within the framework of the domestic engineering development strategy.

Comparative Study of Gasoline Fuel Mixture to Reduce Emissions in the Metropolitan District

In the present investigation, the behavior of fuel consumption was studied due to the high cost of gasoline and its price increase in Ecuador in recent years, for which reason the different mixtures have been studied to obtain lower consumption. The optimum fuel mixture rate for a T18SED e-tec II engine, Multiport Electronic Fuel Injection System (MPFI) between extra gasoline, super gasoline, and ethanol was obtained on two urban roads in the city of Quito (Ecuador). For the first test, mixtures of 10% super gasoline and 90% extra gasoline were made, and so on, for the following tests: (20–80), (30–70), (40–60), (50–50), (60–40), (70–30), (80–20), and (90–10) % super and extra gasoline. Then, mixtures between super gasoline and ethanol and extra gasoline and ethanol with concentrations of 5% and 10% were made. The results showed a low consumption on Maldonado Avenue with the 20% extra and 80% super mixtures obtaining a value of 2.9 L, while the mixture that presented a higher consumption was 100% extra of 3.4 L. At the end of each test, the fuel tank was completely drained, and the engine control unit (ECU) was reset for each test. The data acquisition was carried out through an OBD II (on-board diagnostic system) installed in each of the tests.

Вплив показників якості палива та технічний стан автомобіля під час руху

In this article, the importance of the interaction between fuel quality and the technical condition of the vehicle is examined to determine its dynamic characteristics and road safety. The research is based on the analysis of the impact of these factors on the vehicle during operation and maneuver execution, especially during overtaking maneuvers where having sufficient engine power reserve to achieve the required level of acceleration is crucial. It is noted that understanding the reasons for changes in dynamic properties is critical, as a reduction in the engine power reserve of the vehicle can complicate the safe execution of overtaking maneuvers. The main focus of the work is placed on the necessity of considering these changes in the vehicle's mobility control systems. The article also includes an analysis of recent research in the field of the interaction between fuel and the technical condition of the vehicle. Research in this area is aimed at understanding the interaction between fuel parameters and the technical characteristics of vehicles to make transportation more efficient, extend the service life of vehicles, and address environmental challenges. The article concludes with findings that emphasize the effectiveness of the developed coefficient for considering the technical condition of the vehicle and fuel quality to enhance the accuracy of safety systems and predict the potential acceleration of the vehicle in traffic. The proposed coefficient will make it possible to increase the accuracy of predicting the potential acceleration of the car by the on-board system. Additionally, the possibility of using this coefficient to detect changes in fuel quality and the technical condition of the vehicle is discussed, providing drivers with information through onboard diagnostic systems and measurement complexes to take appropriate actions.

Framework for Building Low-Cost OBD-II Data-Logging Systems for Battery Electric Vehicles

With the electrification of transport (BEVs) and the growing benefits of smart vehicles, there is a need for a simple solution to perform real-time monitoring of the BEV and its battery for diagnostics and coordinated charging. The On-Board Diagnostics (OBD) system, originally designed for internal combustion engine cars (ICE), can be used to extract the necessary BEV data. This paper presents a developed framework for a low-cost solution to online monitoring of BEVs. A Raspberry Pi Zero W, along with other auxiliary components, was installed in two Hyundai Ioniq Battery Electric cars to communicate with the vehicles via the OBD-II port. A python script was developed to periodically request the vehicle data by sending various Parameter IDs to the vehicles and storing the raw response data. A web server was created to process the hexadecimal encoded data and visualize the data on a dashboard. The key parameters, such as the battery state of health (SOH), state of charge (SOC), battery temperature, cell voltages and cumulative energy consumption, were successfully captured and recorded, which can now facilitate trending for battery diagnostics and future integration with smart chargers for coordinated charging.

A fuel-consumption based window method for PEMS NOx emission calculation of heavy-duty diesel vehicles: Method description and case demonstration

Due to the lack of engine reference torque and the accumulated work of reference transient cycle, the work based window (WBW) method for portable emission measurement system test data processing cannot be used for vehicle emission assessment in the current on-board diagnostics (OBD) system in China. In this work, a fuel-consumption based window (FBW) method was proposed to imitate a WBW method procedure by using fuel consumption rate as an alternative parameter to scale the window so the entire procedure can be based on the attainable data items in the OBD system. Some key issues regarding converting WBW method to FBW method, including window separation, window average power ratio calculation and specific NOx emission conversion from mg/kg. fuel to mg/kW.h, were solved by linking the 100-km fuel consumption and the average vehicle specific power of China World Transient Vehicle Cycle test. The comparison between the FBW and WBW methods on the NOx emission calculation results shows that the number of all windows, the number of valid windows, and the thresholds for >50% valid windows are quite similar for WBW and FBW methods. The estimation accuracy of average power ratio for the FBW method depends on the value of transmission efficiency of vehicle driveline. The deviations of 90% specific NOx emission in mg/kW.h between the two methods are smaller than 6% for the cases investigated in the present work.

Protocols for Secure Remote Access to Vehicle Onboard Diagnostic Systems in Smart Cities

The onboard diagnostic system (OBD) is almost standard on every modern vehicle. By exploiting the availability of wireless OBD dongles, vehicles can be assessed by the transportation authority and drivers to ensure compliance with emissions regulations. A vehicle’s OBD system can be remotely accessed by a fog node to retrieve a variety of the vehicle’s internal status and sensor readings. Such information can be shared with the transportation authority for registration renewal without the need for visiting emission stations. However, such automation comes at the risk of malicious intrusion into the OBD system by an attacker who aims to gain access to a vehicle’s internal network and control the vehicle. This article tackles this serious issue and proposes protocols for mutual authentication and securing the wireless connection between the OBD dongle, fog node, and authority. The robustness of the proposed protocols is verified using the Automated Validation of Internet Security Protocols and Applications (AVISPA) toolset.

Application of a Digital Twin Virtual Engineering Tool for Ground Vehicle Maintenance Forecasting

<div class="section abstract"><div class="htmlview paragraph">The integration of sensors, actuators, and real-time control in transportation systems enables intelligent system operation to minimize energy consumption and maximize occupant safety and vehicle reliability. The operating cycle of military ground vehicles can be on- and off-road in harsh weather and adversarial environments, which demands continuous subsystem functionality to fulfill missions. Onboard diagnostic systems can alert the operator of a degraded operation once established fault thresholds are exceeded. An opportunity exists to estimate vehicle maintenance needs using model-based predicted trends and eventually compiled information from fleet operating databases. A digital twin, created to virtually describe the dynamic behavior of a physical system using computer-mathematical models, can estimate the system behavior based on current and future operating scenarios while accounting for past effects. In this manner, the collection of real-time data of the physical vehicle can be compared with the virtual counterpart to assess the likelihood of degraded operation and recommend maintenance. This paper creates a digital twin for an off-road tracked ground vehicle with an accompanying parameter database. A modular architecture enables different design reconfigurations to evaluate various chassis subsystems and vehicle-ground mobility interfaces. A preventive maintenance algorithm is applied to monitor the operating behavior of the vehicle. The prediction tool, operating in parallel with the digital twin, may use model-based and sensory signal condition indicators to monitor vehicle performance. A case study investigates two operating scenarios: a virtual wheeled suspension system is degraded; and a virtual tracked vehicle experiences missing trackpads, which subtly alter the performances. The numerical results will offer insight into the pathway to begin creating a digital twin-based maintenance forecasting strategy.</div></div>