Article
Engineering, Mechanical
Lorenzo Mosconi, Flavio Farroni, Aleksandr Sakhnevych, Francesco Timpone, Fabio S. Gerbino
Summary: This work describes the development of a vehicle state estimator that can be used in real-time based on the data acquisitions available within the vehicle CAN bus infrastructure. The proposed algorithm takes into account various dynamics and interaction torques to provide accurate estimations of road slope, banking angles, and physical characteristics of tire/road interaction.
VEHICLE SYSTEM DYNAMICS
(2023)
Article
Automation & Control Systems
Stefano Carnier, Matteo Corno, Sergio M. Savaresi
Summary: This paper presents a robust sideslip estimation method for unknown road grip conditions. It utilizes a hybrid kinematic-dynamic closed-loop observer with a friction classifier to adapt to rapid changes in road conditions. Experimental results show that the approach accurately estimates sideslip on different road surfaces with an error of less than 1.5 degrees.
JOURNAL OF DYNAMIC SYSTEMS MEASUREMENT AND CONTROL-TRANSACTIONS OF THE ASME
(2023)
Article
Energy & Fuels
Himadri Sekhar Bhattacharyya, Amalendu Bikash Choudhury, Chandan Kumar Chanda
Summary: This paper focuses on the battery management system (BMS) and the calculation of state of charge (SOC) in lithium-ion batteries. By using the electrical equivalent circuit model (EECM) and algorithms such as extended Kalman filter (EKF) and dual extended Kalman filter (DEKF), a fairly accurate estimate of SOC can be obtained. The impact of voltage and current sensor bias on SOC is also investigated, and the effectiveness of the algorithms is validated under different conditions.
INTERNATIONAL JOURNAL OF ENERGY RESEARCH
(2022)
Article
Chemistry, Analytical
Rafael Carbonell, Angel Cuenca, Vicente Casanova, Ricardo Piza, Julian J. Salt Llobregat
Summary: This paper proposes a path-following motion control method for a two-wheel drive unmanned ground vehicle (UGV), utilizing dual-rate extended Kalman filtering techniques to estimate fast-rate non-available position and orientation measurements, and designing a fast-rate dynamic controller that outperforms the slow-rate counterpart.
Article
Engineering, Chemical
Hui Zhang, Zichao Yang, Huiyuan Xiong, Taohong Zhu, Zhineng Long, Weibin Wu
Summary: Vehicle mass estimation is a crucial issue in autonomous vehicle control due to the nonlinearity of vehicle dynamics between states. This study proposes a transformer aided adaptive extended Kalman filter to improve the accuracy and stability of estimation. By introducing a transformer-based estimator and an adaptive law based on neural network training data, the proposed method achieves accurate and stable estimation. Simulation tests demonstrate the superior performance of the proposed method in terms of accuracy and stability.
Article
Engineering, Mechanical
Giulio Reina, Antonio Leanza, Giacomo Mantriota
Summary: Advanced control and driving assistance systems in modern vehicles ensure higher safety and performance standards. Virtual sensing using physical models to infer tyre forces and slip angles is a promising alternative. Model-based observation, particularly with Kalman filters, shows better accuracy and stability compared to traditional methods like Extended Kalman filter.
VEHICLE SYSTEM DYNAMICS
(2022)
Article
Energy & Fuels
Xin Lai, Yunfeng Huang, Xuebing Han, Huanghui Gu, Yuejiu Zheng
Summary: A novel SOE estimation method using PF and EKF algorithms is proposed in this study, which is able to improve accuracy and robustness by identifying battery model parameters at different temperatures. Experimental results show that the maximum error of the proposed algorithm is less than 3% under dynamic conditions and can quickly converge to its reference trajectory even with large initial errors in SOE and total available energy.
JOURNAL OF ENERGY STORAGE
(2021)
Article
Mathematics
Qian Zhang, Yifan Xu, Xueyun Wang, Zelong Yu, Tianyi Deng
Summary: This article presents an innovative method for online calibration of the pitot tube and estimation of wind field, with analysis of the observability of EKF and experimental validation showing the feasibility and effectiveness of the proposed approach.
Article
Chemistry, Analytical
Tzu-Yi Chuang, Xiao-Dong Zhang, Chih-Keng Chen
Summary: This study determines the roll angle for a two-wheeled single-track vehicle during cornering by using Kalman filter theory and signals from an IMU sensor to estimate the yaw rate and roll angle through measuring acceleration and angular velocity. Experimental results show that this estimator has reliability and accuracy.
Article
Engineering, Mechanical
Shouvik Chakraborty, Anindita Sengupta, Ashoke Sutradhar
Summary: This paper presents a modular approach based on AUKF to estimate lateral vehicle dynamics and tyre forces. Through simulation and real vehicle dataset validation, the results show that the proposed scheme has higher accuracy and less computational time compared to non-modular observers.
INTERNATIONAL JOURNAL OF VEHICLE DESIGN
(2022)
Article
Engineering, Electrical & Electronic
Yangtianze Tao, Stephen Shing-Toung Yau
Summary: In this paper, we propose a novel outlier-robust iterative extended Kalman filtering (OR-IEKF) framework based on nonlinear regression formulation of update step. The OR-IEKF framework introduces a new Kalman-type update step with reweighted prediction covariance and reweighted observation noise covariance, which can eliminate large outliers caused by unknown outlier noises. By employing robust cost functions, three algorithms are derived to solve the special nonlinear regression problems. The performances of these new filters are evaluated in a simulation study of a nonlinear system.
IEEE SIGNAL PROCESSING LETTERS
(2023)
Article
Engineering, Electrical & Electronic
Motoya Suzuki
Summary: Slip angle estimation is widely used in mobile robotics. In this study, a linear Kalman filter-based method is proposed to estimate the slip angle, which eliminates the wave distortion by adjusting the Kalman gain.
IEEJ TRANSACTIONS ON ELECTRICAL AND ELECTRONIC ENGINEERING
(2023)
Article
Automation & Control Systems
Emir Hrustic, Rayen Ben Abdallah, Jordi Vila-Valls, Damien Vivet, Gael Pages, Eric Chaumette
Summary: This paper discusses the use of linearly constrained KF for robust nonlinear filtering under mismatched process and measurement models, introducing a new linearly constrained extended KF (LCEKF) for mitigating parametric modeling errors. The performance improvement of the new LCEKF for robust vehicle navigation is demonstrated through numerical results.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2021)
Article
Engineering, Marine
Wenhao Xu, Jianmin Yang, Handi Wei, Jinghang Mao, Haining Lu, Xin Li
Summary: A localization algorithm named 'ESKF-slip' was developed and validated for deep-sea mining vehicles in this study. A localization system was established based on the algorithm for a newly designed deep-sea mining vehicle named Pioneer 1. Sea trials in the South China Sea demonstrated the feasibility and applicability of the proposed algorithm in obtaining accurate localization results for the deep-sea mining vehicle.
Article
Chemistry, Analytical
Minseok Ok, Sungsuk Ok, Jahng Hyon Park
Summary: This paper proposes a method for vehicle attitude estimation using a convolutional neural network and a dual-extended Kalman filter. Experimental results show that this method can accurately estimate the vehicle's attitude and acceleration information, improving modeling accuracy.
Article
Energy & Fuels
Giulia Sandrini, Marco Gadola, Daniel Chindamo
Summary: The automotive sector is increasingly shifting towards electric powertrains due to environmental pollution and limited availability of fossil fuels. A simulation tool has been developed to analyze the performance of electric and hybrid powertrains, aiming to accelerate the design process and reduce costs. Validation based on real vehicles shows accuracy and reliability of the model.
Article
Energy & Fuels
Daniel Chindamo, Marco Gadola, Emanuele Bonera, Paolo Magri
Summary: Understanding the energy exerted on tires is crucial in motorsport, especially in feeder categories like Formula 1 where tire numbers are limited to control costs. By knowing how setup changes affect tires and providing a scientific method for tire management, race engineers can maintain high performance levels throughout the entire race weekend.
Article
Automation & Control Systems
Michele Schiavo, Fabrizio Padula, Nicola Latronico, Massimiliano Paltenghi, Antonio Visioli
Summary: This study proposes a methodology for patient-individualized tuning of a PID controller in general anesthesia, showing increased robustness with a slight increment in disturbance rejection time compared to population-based tuning.
JOURNAL OF PROCESS CONTROL
(2022)
Article
Computer Science, Interdisciplinary Applications
Michele Schiavo, Fabrizio Padula, Nicola Latronico, Massimiliano Paltenghi, Antonio Visioli
Summary: This study aims to design a PID-based control system for regulating the depth of hypnosis in total intravenous anesthesia and takes into account the clinical practice. The experimental results demonstrate that the control system can achieve adequate anesthesia without manual intervention from the anesthesiologist.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2022)
Article
Energy & Fuels
Giulia Sandrini, Daniel Chindamo, Marco Gadola
Summary: This paper presents a regenerative braking logic that maximizes energy recovery during braking while ensuring vehicle stability. By exploiting the regenerative torque of the electric motor(s), the logic avoids wheel locking and integrates with the traditional braking system if needed. The priority of the logic is to maximize energy recovery, followed by optimal braking distribution. Simulation tests on different drivetrains show significant fuel consumption reductions compared to other common logics.
Article
Energy & Fuels
Laura Zecchi, Giulia Sandrini, Marco Gadola, Daniel Chindamo
Summary: This study develops a mathematical model for simulating a fuel cell hybrid powertrain, which is versatile and modular for testing new solutions.
Article
Energy & Fuels
Marco Gadola, Daniel Chindamo, Paolo Magri, Giulia Sandrini
Summary: Porpoising is a well-known problem affecting the dynamic behavior of 2022 Formula 1 racing cars, caused by the extreme sensitivity of aerodynamic loads to ride height variations. Race engineers are still struggling to cope with this phenomenon and its consequences halfway through the season, aiming to find a balance between vehicle performance and stability. Two models based on real-world data have been introduced to recreate the porpoising phenomenon and guide setup changes, despite the topic's highly confidential nature making quantitative validation impossible.
Article
Automation & Control Systems
Michele Schiavo, Fabrizio Padula, Nicola Latronico, Massimiliano Paltenghi, Antonio Visioli
Summary: This paper presents the first experimental results of using an event-based PID regulator for closed-loop control of general anesthesia. The control system uses the bispectral index scale as feedback and regulates the coadministration of propofol and remifentanil. The experiments were conducted on fourteen patients, representing routine clinical practice. The results show that the event-based control system performs consistently with care standards, providing a noise-free infusion profile that mimics anesthesiologists' behavior and reduces control effort on infusion pumps. This proposed solution represents a significant step toward the acceptance and diffusion of closed-loop control systems in routine clinical practice.
CONTROL ENGINEERING PRACTICE
(2023)
Article
Energy & Fuels
Giulia Sandrini, Marco Gadola, Daniel Chindamo, Andrea Candela, Paolo Magri
Summary: Nowadays, reducing vehicles' energy consumption is crucial, especially for electric vehicles. Lightweighting, or reducing the vehicle mass, can effectively decrease use-phase impacts and energy consumption. This study analyzes the parameters that influence lightweighting results and provides guidelines for creating a suitable vehicle model. Through simulation, it is found that factors such as rolling resistance, battery characteristics, aerodynamic coefficients, and transmission efficiency significantly affect lightweighting outcomes, while inertia contributions are negligible. The study also considers the variation of driving cycles.
Proceedings Paper
Automation & Control Systems
Dean Thomson, Fabrizio Padula
Summary: This paper proposes using a temperature control problem to introduce fractional modeling and control to students. By using a heated aluminum rod in a simple laboratory setup, students can control the rod's temperature using different control algorithms, experiencing the benefits of fractional control and exploring advanced control paradigms.
Article
Mathematics, Interdisciplinary Applications
Helber Meneses, Orlando Arrieta, Fabrizio Padula, Antonio Visioli, Ramon Vilanova
Summary: This paper discusses the design of a control system based on fractional order models and controllers. The fractional order models can represent various dynamic behaviors, and the optimization and fitting functions are used to tune the controller parameters, achieving a balance between robustness and performance.
FRACTAL AND FRACTIONAL
(2022)