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"Automotive sensors"
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Performance Evaluation of MEMS-Based Automotive LiDAR Sensor and Its Simulation Model as per ASTM E3125-17 Standard
Measurement performance evaluation of real and virtual automotive light detection and ranging (LiDAR) sensors is an active area of research. However, no commonly accepted automotive standards, metrics, or criteria exist to evaluate their measurement performance. ASTM International released the ASTM E3125-17 standard for the operational performance evaluation of 3D imaging systems commonly referred to as terrestrial laser scanners (TLS). This standard defines the specifications and static test procedures to evaluate the 3D imaging and point-to-point distance measurement performance of TLS. In this work, we have assessed the 3D imaging and point-to-point distance estimation performance of a commercial micro-electro-mechanical system (MEMS)-based automotive LiDAR sensor and its simulation model according to the test procedures defined in this standard. The static tests were performed in a laboratory environment. In addition, a subset of static tests was also performed at the proving ground in natural environmental conditions to determine the 3D imaging and point-to-point distance measurement performance of the real LiDAR sensor. In addition, real scenarios and environmental conditions were replicated in the virtual environment of a commercial software to verify the LiDAR model’s working performance. The evaluation results show that the LiDAR sensor and its simulation model under analysis pass all the tests specified in the ASTM E3125-17 standard. This standard helps to understand whether sensor measurement errors are due to internal or external influences. We have also shown that the 3D imaging and point-to-point distance estimation performance of LiDAR sensors significantly impacts the working performance of the object recognition algorithm. That is why this standard can be beneficial in validating automotive real and virtual LiDAR sensors, at least in the early stage of development. Furthermore, the simulation and real measurements show good agreement on the point cloud and object recognition levels.
Journal Article
Integrated Vehicle Health Management
Following the best seller, Integrated Vehicle Health Management: Perspectives on an Emerging Field, the new title Integrated Vehicle Health Management: The Business Case Theory and Practice takes the subject to the next level. This time it addresses the commercial justification for the adoption of a new modus operandi in asset health management, and its impact on business strategy and servitization of technology. Edited by Dr. Ian Jennions, Director of the IVHM Center at Cranfield University in the U.K., the book tackles the most important questions on the transformation of business from selling a product, and deriving future income from spare part sales, to selling a service in which income is received in return for effective maintenance of the asset. The resulting service business requires a much deeper understanding of how the product is used and should be maintained, thus providing the rationale for Integrated Vehicle Health Management- IVHM. Chapter highlights include: -How to calculate the return on investment of an IVHM system -How real options can be used for decision making -How the availability of prognostic information affects maintenance -The business potential of structural health monitoring in aeronautics Integrated Vehicle Health Management: The Business Case Theory and Practice includes interviews with manufacturers and suppliers on how they are marketing one-of-a-kind services, and opening up new and sustainable revenue streams. Case studies are also introduced to demonstrate the real value of condition-based maintenance, the advantage of cost avoidance and risk mitigation for high-value assets. The objective is to provide the tools and techniques for constructing a business case while also providing some of the context in which these variables are framed. Directed at industry professionals as well as researchers and students, Integrated Vehicle Health Management: The Business Case Theory and Practice fills an important gap in this emerging body of knowledge which unites the technical and the business aspects of a paradigm shift.
eBook
On-Road Evaluation of Unobtrusive In-Car Respiration Monitoring
This paper introduces and evaluates an innovative sensor for unobtrusive in-car respiration monitoring, mounted on the backrest of the driver’s seat. The sensor seamlessly integrates into the vehicle, measuring breathing rates continuously without requiring active participation from the driver. The paper proves the feasibility of unobtrusive in-car measurements over long periods of time. Operation of the sensor was investigated over 12 participants sitting in the driver seat. A total of 107 min of driving in diverse conditions with overall coverage rate of 84.45% underscores the sensor potential to reliably capture physiological changes in breathing rate for fatigue and stress detection.
Journal Article
Fuel Level Estimation in Tank of Truck in Motion
The paper presents the results of a case study on estimating the fuel level in the tank of a motor vehicle. A method based on the concept of particle filtering of noisy measurement data is proposed. The algorithm designed using the Sequential Monte Carlo method with Sequential Importance Sampling is combined with classical digital filters used for signal filtering. In the simulations, real data obtained by measuring fuel levels in the tanks of TIR heavy trucks from one of the Polish trucking companies are used. The performance of the applied method was considered in various measurement situations, such as refueling, driving on an uneven road surface, driving on steep roads, and fading of the measurement signals.
Journal Article
Product Integration of Established Crash Sensors for Safety Applications in Lightweight Vehicles
The functionality of products increases when more sensors are used. This trend also affects future automobiles and becomes even more relevant in connected and autonomous applications. Concerning automotive lightweight design, carbon fibre-reinforced polymers (CFRP) are suitable materials. However, their drawbacks include the relatively high manufacturing costs of CFRP components in addition to the difficulty of recycling. To compensate for the increased expenditure, the integration of automotive sensors in CFRP vehicle structures provides added value. As a new approach, established sensors are integrated into fibre-reinforced polymer (FRP) structures. The sensors are usually mounted to the vehicle. The integration of sensors into the structure saves weight and space. Many other approaches specifically develop new sensors for integration into FRP structures. With the new approach, there is no need for elaborate development of new sensors since established sensors are used. The present research also showed that the range of applications of the sensors can be extended by the integration. The present paper outlines the functional behaviour of the integrated sensor utilized for crashing sensing. First of all, the integration quality of the sensor is relevant. Different requirements apply to the usual mounting of the sensor. The self-sensing structure must fulfil those requirements. Moreover, unfamiliar characteristics of the new surrounding structure might affect the sensing behaviour. Thus, the sensing behaviour of the self-sensing composite was analyzed in detail. The overarching objective is the general integration of sensors in products with reasonable effort.
Journal Article
Next-Generation Pedal: Integration of Sensors in a Braking Pedal for a Full Brake-by-Wire System
This article presents a novel approach to designing and validating a fully electronic braking pedal, addressing the growing integration of electronics in vehicles. With the imminent rise of brake-by-wire (BBW) technology, the brake pedal requires electronification to keep pace with industry advancements. This research explores technologies and features for the next-generation pedal, including low-power consumption electronics, cost-effective sensors, active adjustable pedals, and a retractable pedal for autonomous vehicles. Furthermore, this research brings the benefits of the water injection technique (WIT) as the base for manufacturing plastic pedal brakes towards reducing cost and weight while enhancing torsional stiffness. Communication with original equipment manufacturers (OEMs) has provided valuable insights and feedback, facilitating a productive exchange of ideas. The findings include two sensor prototypes utilizing inductive technology and printed-ink gauges. Significantly, reduced power consumption was achieved in a Hall-effect sensor already in production. Additionally, a functional BBW prototype was developed and validated. This research presents an innovative approach to pedal design that aligns with current electrification trends and autonomous vehicles. It positions the braking pedal as an advanced component that has the potential to redefine industry standards. In summary, this research significantly contributes to the electronic braking pedal technology presenting the critical industry needs that have driven technical studies and progress in the field of sensors, electronics, and materials, highlighting the challenges that component manufacturers will inevitably face in the forthcoming years.
Journal Article
Advancements in noise reduction for wheel speed sensing using enhanced LSTM models
This research presents an Enhanced Long Short-Term Memory (LSTM) deep learning model for robust noise reduction in automotive wheel speed sensors. While wheel speed sensors are pivotal to vehicle stability, high-intensity or non-stationary noise often degrades their performance. Traditional filtering methods, including adaptive approaches and basic digital signal processing, frequently underperform under complex conditions. The proposed model addresses these limitations by incorporating an attention mechanism that selectively emphasizes transient high-noise frames, preserving essential rotational information. Comprehensive experiments, supported by Variational Mode Decomposition (VMD) and the Hilbert-Huang Transform (HHT), demonstrate that the Enhanced LSTM surpasses conventional techniques and baseline LSTM architectures in suppressing interference. T results yield significantly improved metrics across varying noise intensities, confirming both efficacy and stability. Although factors such as computational cost and the need for extensive labeled data remain, the Enhanced LSTM shows strong potential for real-time applications in wheel speed sensing. This work offers valuable insights into advanced noise mitigation and serves as a foundation for future deep learning research in complex automotive signal processing tasks.
Journal Article
A Magnetoelectric Automotive Crankshaft Position Sensor
The paper is devoted to the possibility of using magnetoelectric materials for the production of a crankshaft position sensor for automobiles. The composite structure, consisting of a PZT or LiNbO3 piezoelectric with a size of 20 mm × 5 mm × 0.5 mm, and plates of the magnetostrictive material Metglas of the appropriate size were used as a sensitive element. The layered structure was made from a bidomain lithium niobate monocrystal with a Y + 128° cut and amorphous metal of Metglas. Various combinations of composite structures are also investigated; for example, asymmetric structures using a layer of copper and aluminum. The output characteristics of these structures are compared in the resonant and non-resonant modes. It is shown that the value of the magnetoelectric resonant voltage coefficient was 784 V/(cm·Oe), and the low-frequency non-resonant magnetoelectric coefficient for the magnetoelectric element was about 3 V/(cm·Oe). The principle of operation of the position sensor and the possibility of integration into automotive systems, using the CAN bus, are examined in detail. To obtain reliable experimental results, a special stand was assembled on the basis of the SKAD-1 installation. The studies showed good results and a high prospect for the use of magnetoelectric sensors as position sensors and, in particular, of a vehicle’s crankshaft position sensor.
Journal Article
Research on the Sensitivity of Automotive Sensors under the Background of 5G
With the continuous development of automotive electronics, automotive sensing technology has also appeared and has been more and more widely used. As an important part of the automotive electronic control system, automotive sensors not only need to collect information, but also transmit information. The automobile sensor first needs to convert the automobile operating condition information into electrical signals and then transmit it to the central control unit, in order to make the engine reach the best working condition. In addition, automotive sensors can also perform accurate and real-time measurement and control for information such as pressure, temperature, speed, photoelectricity and flow rate, which greatly improves the effectiveness of information processing. As a factor that can affect the safe operation of a car, the quality of the car sensor plays a direct role. Therefore, in order to ensure the safe operation of automobiles, strict requirements on the accuracy, stability, responsiveness, shock resistance and service life of automobile sensors are required. The development of modern cars is moving towards a safer and more comfortable perspective and the key to achieving this goal lies in the development of sensors. At present, the development of sensors mainly depends on the development of new sensors and the integration, intelligence and multifunction of sensors. Realize the improvement of the sensor's working accuracy and response speed and the ability to adapt to different environments. Therefore, studying the application of sensors in the current automotive field is of great significance to the future development of the automotive field and the sensor field.
Journal Article