Mohammad Bahari’s Post

📃 Exciting News! We are delighted to announce the publication of our latest paper, entitled "Novel Methodology for Integrated Actuator and Sensors Fault Detection and Estimation in an Active Suspension System", in the journal IEEE Transactions on Reliability. Authors: Miguel Meléndez Useros, Manuel Jiménez Salas, Fernando Viadero Monasterio and Maria Jesus Lopez Boada. This work is part of the grant PID2022-136468OB-I00 funded by MICIU/AEI/ 10.13039/501100011033 and by ERDF, EU. While previous studies have focused on individual fault identification and estimation in Active Suspension Systems (ASSs), our paper breaks new ground by proposing an innovative fault diagnosis scheme that enables the integrated detection and estimation of both actuator and sensor faults. Key highlights of our methodology include: 🔍 Utilization of two unknown input observers (UIOs) for separate estimation of actuator and sensor faults. 🔄 Implementation of a switch-off mechanism for actuators to prevent coupling between estimations, facilitating the distinction and isolation of coupled deflection sensor and actuator faults. 🚩 Generation of signal flags to pinpoint the faulty suspension component and enhance the accuracy of UIO estimations. For those wishing to pursue further investigation of our findings, the paper is available in open access format via the attached URL. #FaultDetection #ActiveSuspensionSystems #Research https://lnkd.in/dKg2bVNj

Our concept for a market novelty - more efficient and fail-safe industrial drives through #TinyML and #GaN semiconductors ⚙ From permanently operated production lines to electrified transportation – electric drives are the system’s centerpiece and therefore critical to failure as well as primarily responsible for efficiency. To get closer to the requirement for absolute reliability of electrical drives and the power semiconductors used to drive them, intelligent controllers require the capability to monitor and interpret the state of the system components in real time. In the strategic research project PowerCare (www.power-care.org), Fraunhofer will combine new, highly efficient GaN semiconductors and a AI-capable motor controller for integrated realtime failure monitoring. Have a look: https://lnkd.in/e_yuaRDM Fraunhofer-Institut für Mikroelektronische Schaltungen und Systeme IMS Fraunhofer IISB Fraunhofer ISIT

New Publication: Roadside Sensors for Traffic Management Knowledge of modern, state-of-the-practice traffic flow sensors provides traffic managers, researchers, and students an understanding of the operation, strengths, and limitations of current sensor technologies and enables them to make an informed decision as to which is appropriate for a particular application. Accordingly, this paper describes intrusive and non-intrusive traffic flow sensor technologies in use today, their applications and selection criteria, and typical output data. Furthermore, it provides examples of representative sensor models. The technologies discussed are mature with respect to curr...

I'm excited to announce the publication of my latest paper titled "Development of a Multiturn Linear Variable Reluctance Resolver With Integrated Ferromagnetic Core" in IEEE Sensors Journal! 📡✨ #LinearMotors are increasingly used across various industries, and linear position sensors play a crucial role in their control systems. Among these sensors, the linear resolver stands out as an ideal option for harsh environments. In applications requiring high accuracy, multispeed resolvers are often preferred. This research introduces a multiturn linear variable reluctance resolver (LVRR) with an integrated ferromagnetic core, offering enhanced precision and robustness in position sensing. We explore the unique advantages of this design, which include improved accuracy and reliability—key factors for industrial use. A special thanks to Prof. Zahra Nasiri-Gheidari for their invaluable support and guidance throughout this work. You can access the paper here: ✅ https://lnkd.in/eG_je68j #Resolvers #PositionSensing #IEEE #Innovation #IndustrialApplications

I am very happy to share the paper that presents my research: “Sensorless Control of Induction Motor Based on Rotors Slot Harmonics and Digital Adaptive Filters”, in #IEEE Transactions on Industry Applications, authored by Aleksandar Milić and Slobodan Vukosavić. This paper provides a speed estimator based on rotor slot harmonics. The estimator and the derived analytical model can be used for stand-alone applications, for the design of the high-performance sensorless closed-loop control, field-oriented control, etc. The estimator provides high accuracy and low estimation delay. Sensorless operation is demonstrated with a high closed-loop bandwidth and disturbance rejection of 100% of the rated torque. The solution is not limited to special applications and can be applied to any induction machine capable of generating rotor slot harmonics, without any hardware or software requirements. The performance of the presented design can be guaranteed down to very low speeds where the rotor slot harmonic is represented with a minimum of 5 ADC quantization levels. Stability analysis of the estimator and the closed-loop system are also provided. The paper is available via #IEEEXplore at: https://lnkd.in/dsVPhzQF I want to thank my supervisors Prof. Slobodan Vukosavić for great mentorship and support during this research. I hope that this paper will inspire further research in this interesting field. #drives #sensorless #digitalcontrol #pll #digitalfilters

My new article has been published in IEEE Sensors Journal. If you are interested in this topic, write to me and I will send you the preprint

🌟 Exciting News! 🚗⚡️ Our latest publication in IEEE Access explores cutting-edge advancements in securing electric vehicle (EV) performance through machine learning-driven fault detection and classification. 📝 In this paper, we delve into the crucial role of interfacing connections in EVs, particularly focusing on the link between the 3-ϕ inverter output and the brushless DC (BLDC) motor. By leveraging machine learning tools, including Decision Tree, Logistic Regression, AdaBoost, and more, we aim to detect and classify faults in these connections during operational modes in EV platforms. 🔍 Our research considers various fault scenarios, such as double-line and three-phase faults, and utilizes datasets encompassing critical parameters like current supplied to the BLDC motor, modulated DC voltage, output speed, and more. Through rigorous testing and comparison, we evaluate the efficiency and reliability of our proposed fault detection and classification approaches. 🙏 Special thanks to Md. Ilius Hasan Pathan for his invaluable collaborations! 📈 Join us in revolutionizing EV technology and ensuring its robustness for a sustainable future! Read the full paper here: [link shared below]

Swisspod Technologies brings a revolutionary change on hyperloop propulsion systems (levitation and stability), which enables minimum CAPEX and OPEX on the infrastructure by substantially lowering the end effect of an SLIM. This means a real passive hyperloop infrastructure. Traditional LIMs suffer of a degradation of performance at high speeds (drastic reduction of thrust) which in the literature is called end effect. The proposed theory uses the magnetic Reynolds number to illustrate that end effect is linked with high magnetic Reynolds numbers and then proposes a way of achieving high thrust at high speeds by means of magnetic Reynolds reduction. The proposed LIM has thrust 7 times higher than a traditional LIM at high speed (~1000 km/h). The proposed LIM is suitable for high speed hyperloop systems.

Conventional methods for sensorless motor speed estimation often rely on complex models and state variables, leading to challenges in controller design and stability. In this paper, "A New δ-MRAS Method for Motor Speed Estimation," we introduce a novel approach within the Model Reference Adaptive System (MRAS) framework. By using the motor input impedance angle as a reference state variable, our method decouples the reference and adaptive models, resulting in superior performance across low, high, and zero speeds. This simplified approach enhances analysis, design, and implementation. Comprehensive simulations and real-time hardware-in-the-loop experiments validate its advantages in accuracy, stability, and computational efficiency. This work significantly advances sensorless motor control and drive systems. Read the full paper at: IEEE Transactions on Power Delivery, vol. 36, no. 3, pp. 1903-1906, June 2021, doi: 10.1109/TPWRD.2020.3029422 https://lnkd.in/dac8GRq #MotorControl #SensorlessTechnology #MRAS #ElectricalEngineering #Innovation #SpeedEstimation #IEEE #PowerDelivery #EngineeringResearch #MotorDrives #Automation #TechInnovation #ResearchAndDevelopment

🔍📄 Check out our newly published paper on the consideration of #thermal #ageing effects implemented in LPTNs for the adaptation of #digitaltwins during the #eMotor lifecycle. This work was presented in the ICEM 2024 26TH International Conference on Electrical Machines. Thanks to all collaborators in GKN Automotive and Universidade da Coruña Centro de Investigación en Tecnoloxías Navais e Industriais da Universidade da Coruña - CITENI.