Pub Date : 2025-01-01Epub Date: 2025-12-05DOI: 10.1016/j.ifacol.2025.11.816
Marco Bignardi , Nikos Tsoulias , Andreas Heiß , Dimitrios S. Paraforos
Climate change significantly impacts viticulture by harming plant and fruit growth, resulting in lower quality and storage issues. Therefore, there is growing scientific interest in the carbon fluxes of vineyard management activities, including efforts to measure carbon capture and storage in annual biomass. Precision Viticulture and Machine Vision techniques can help assess variations in vines’ biomass, which relate to the vines’ carbon balance. The present study examined the feasibility of a light detection and ranging (LiDAR) for vines’ (Vitis vinifera L. cv. Riesling) annual biomass reconstruction and its role in the annual carbon cycle. The leaves dry weight showed a high correlation coefficient of R² = 0.87 with the LiDAR-based leaf area estimation. Thus, making the proposed sensing system reliable for biomass elemental carbon assessment. Nevertheless, no significant correlation was found for the monitoring of leaf area/fruit ratio. The proposed study showcases the potential and the limits of LiDAR-based vine biomass assessment.
气候变化严重影响葡萄种植，损害植物和果实生长，导致质量下降和储存问题。因此，人们对葡萄园管理活动的碳通量越来越感兴趣，包括测量年生物量中碳捕获和储存的努力。精密葡萄栽培和机器视觉技术可以帮助评估葡萄生物量的变化，这与葡萄的碳平衡有关。本研究探讨了葡萄（Vitis vinifera L. cv）的光探测和测距（LiDAR）的可行性。雷司令)年生物量重建及其在年碳循环中的作用。叶片干重与基于激光雷达的叶面积估算具有较高的相关系数R²= 0.87。因此，使所提出的传感系统可靠的生物质元素碳评估。然而，叶面积/果比的监测没有发现显著的相关性。该研究展示了基于激光雷达的藤本植物生物量评估的潜力和局限性。
{"title":"Evaluation of Vine’s Annual Carbon Stocks by Means of LiDAR-Based 3D Reconstruction","authors":"Marco Bignardi , Nikos Tsoulias , Andreas Heiß , Dimitrios S. Paraforos","doi":"10.1016/j.ifacol.2025.11.816","DOIUrl":"10.1016/j.ifacol.2025.11.816","url":null,"abstract":"<div><div>Climate change significantly impacts viticulture by harming plant and fruit growth, resulting in lower quality and storage issues. Therefore, there is growing scientific interest in the carbon fluxes of vineyard management activities, including efforts to measure carbon capture and storage in annual biomass. Precision Viticulture and Machine Vision techniques can help assess variations in vines’ biomass, which relate to the vines’ carbon balance. The present study examined the feasibility of a light detection and ranging (LiDAR) for vines’ (Vitis vinifera L. cv. Riesling) annual biomass reconstruction and its role in the annual carbon cycle. The leaves dry weight showed a high correlation coefficient of R² = 0.87 with the LiDAR-based leaf area estimation. Thus, making the proposed sensing system reliable for biomass elemental carbon assessment. Nevertheless, no significant correlation was found for the monitoring of leaf area/fruit ratio. The proposed study showcases the potential and the limits of LiDAR-based vine biomass assessment.</div></div>","PeriodicalId":37894,"journal":{"name":"IFAC-PapersOnLine","volume":"59 23","pages":"Pages 373-377"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145686014","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper presents a comprehensive investigation into the capability of Large Language Models (LLMs) to successfully complete a semester-long undergraduate control systems course. Through evaluation of 115 course deliverables, we assess LLM performance using ChatGPT under a “minimal effort” protocol that simulates realistic student usage patterns. The investigation employs a rigorous testing methodology across multiple assessment formats, from auto-graded multiple choice questions to complex Python programming tasks and long-form analytical writing. Our analysis provides quantitative insights into AI’s strengths and limitations in handling mathematical formulations, coding challenges, and theoretical concepts in control systems engineering. The LLM achieved a B-grade performance (82.24%), approaching but not exceeding the class average (84.99%), with strongest results in structured assignments and greatest limitations in open-ended projects. The findings inform discussions about course design adaptation in response to AI advancement, moving beyond simple prohibition towards thoughtful integration of these tools in engineering education. Additional materials including syllabus, examination papers, design projects, and example responses can be found at the project website: https://gradegpt.github.io.
{"title":"The Lazy Student’s Dream: ChatGPT Passing an Engineering Course on Its Own","authors":"Gokul Puthumanaillam, Timothy Bretl, Melkior Ornik","doi":"10.1016/j.ifacol.2025.08.049","DOIUrl":"10.1016/j.ifacol.2025.08.049","url":null,"abstract":"<div><div>This paper presents a comprehensive investigation into the capability of Large Language Models (LLMs) to successfully complete a semester-long undergraduate control systems course. Through evaluation of 115 course deliverables, we assess LLM performance using ChatGPT under a “minimal effort” protocol that simulates realistic student usage patterns. The investigation employs a rigorous testing methodology across multiple assessment formats, from auto-graded multiple choice questions to complex Python programming tasks and long-form analytical writing. Our analysis provides quantitative insights into AI’s strengths and limitations in handling mathematical formulations, coding challenges, and theoretical concepts in control systems engineering. The LLM achieved a B-grade performance (82.24%), approaching but not exceeding the class average (84.99%), with strongest results in structured assignments and greatest limitations in open-ended projects. The findings inform discussions about course design adaptation in response to AI advancement, moving beyond simple prohibition towards thoughtful integration of these tools in engineering education. Additional materials including syllabus, examination papers, design projects, and example responses can be found at the project website: <span><span>https://gradegpt.github.io</span><svg><path></path></svg></span>.</div></div>","PeriodicalId":37894,"journal":{"name":"IFAC-PapersOnLine","volume":"59 7","pages":"Pages 213-218"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144989757","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-01Epub Date: 2025-09-04DOI: 10.1016/j.ifacol.2025.08.056
Zhen Shen , Hongyu Li , Jing Yang , Xiaojun Wang , Daniel Horti , Martin Ferenc Dömény , Szatmáry Sára , Adina Chotbaeva , Jimei Ma , Zsombor Zrubka , Fei-Yue Wang
This paper presents a novel educational framework that integrates additive manufacturing (3D printing), social manufacturing platforms, large language models (LLMs), iSTREAMS, and iCDIOS to bridge academic learning, industrial practice, and research innovation. The framework adopts a “learning-by-doing” approach, where students engage in project-driven tasks that span 2D-to-3D modeling, material property optimization, and collaborative problem-solving. By leveraging AI tools for design iteration and real-time feedback, students develop competencies in critical thinking, technical execution, and interdisciplinary collaboration. The framework also emphasizes dynamic assessment mechanisms that combine human evaluation with AI-driven analytics to provide personalized feedback and inform curriculum updates. Through this integrated approach, students are equipped with the skills necessary to navigate the complexities of modern Cyber-Physical-Social Systems (CPSS)-driven industries. A case study is provided to demonstrate the framework’s implementation and its potential to foster interdisciplinary control research and curriculum development, highlighting the synergy between iSTREAMS and iCDIOS in enhancing educational outcomes.
{"title":"Interdisciplinary Control Research and Curriculum Development in CPSS: A Case Study with 3D Printing and Social Manufacturing","authors":"Zhen Shen , Hongyu Li , Jing Yang , Xiaojun Wang , Daniel Horti , Martin Ferenc Dömény , Szatmáry Sára , Adina Chotbaeva , Jimei Ma , Zsombor Zrubka , Fei-Yue Wang","doi":"10.1016/j.ifacol.2025.08.056","DOIUrl":"10.1016/j.ifacol.2025.08.056","url":null,"abstract":"<div><div>This paper presents a novel educational framework that integrates additive manufacturing (3D printing), social manufacturing platforms, large language models (LLMs), iSTREAMS, and iCDIOS to bridge academic learning, industrial practice, and research innovation. The framework adopts a “learning-by-doing” approach, where students engage in project-driven tasks that span 2D-to-3D modeling, material property optimization, and collaborative problem-solving. By leveraging AI tools for design iteration and real-time feedback, students develop competencies in critical thinking, technical execution, and interdisciplinary collaboration. The framework also emphasizes dynamic assessment mechanisms that combine human evaluation with AI-driven analytics to provide personalized feedback and inform curriculum updates. Through this integrated approach, students are equipped with the skills necessary to navigate the complexities of modern Cyber-Physical-Social Systems (CPSS)-driven industries. A case study is provided to demonstrate the framework’s implementation and its potential to foster interdisciplinary control research and curriculum development, highlighting the synergy between iSTREAMS and iCDIOS in enhancing educational outcomes.</div></div>","PeriodicalId":37894,"journal":{"name":"IFAC-PapersOnLine","volume":"59 7","pages":"Pages 255-260"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144989763","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-01Epub Date: 2025-09-04DOI: 10.1016/j.ifacol.2025.08.023
Gabriel Conde , Luis de la Torre , Raquel Dormido , Sebastián Dormido
Laboratory-based learning plays a crucial role in engineering education, especially in fields like automation and control. However, traditional industrial training labs often face challenges in terms of both realism and accessibility, limiting students’ exposure to real-world systems. In this paper, we present the transformation of a complex industrial process control plant into a fully remote-operable laboratory. By integrating new advanced hardware elements, we have enabled remote monitoring and control of the system. These modifications offer students industry-level realism and hands-on experience in industrial automation, accessible from any location. This work demonstrates the potential of the industrial remote lab to enhance engineering education by providing a flexible and realistic learning environment.
{"title":"Adapting an Industrial Control Laboratory for Remote Access⁎","authors":"Gabriel Conde , Luis de la Torre , Raquel Dormido , Sebastián Dormido","doi":"10.1016/j.ifacol.2025.08.023","DOIUrl":"10.1016/j.ifacol.2025.08.023","url":null,"abstract":"<div><div>Laboratory-based learning plays a crucial role in engineering education, especially in fields like automation and control. However, traditional industrial training labs often face challenges in terms of both realism and accessibility, limiting students’ exposure to real-world systems. In this paper, we present the transformation of a complex industrial process control plant into a fully remote-operable laboratory. By integrating new advanced hardware elements, we have enabled remote monitoring and control of the system. These modifications offer students industry-level realism and hands-on experience in industrial automation, accessible from any location. This work demonstrates the potential of the industrial remote lab to enhance engineering education by providing a flexible and realistic learning environment.</div></div>","PeriodicalId":37894,"journal":{"name":"IFAC-PapersOnLine","volume":"59 7","pages":"Pages 60-65"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144989879","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-01Epub Date: 2025-08-06DOI: 10.1016/j.ifacol.2025.07.104
Benjamín Pla , Pau Bares , Andre Aronis , Victor Tomanik
The rapid adoption of Battery Electric Vehicles (BEVs) has been driven by growing environmental awareness and advancements in energy storage technologies. However, lithium-ion cells, central to BEVs, are highly sensitive to temperature variations, requiring effective thermal management to prevent degradation, ensure safety, and optimize performance. This work presents a novel method to replicate the thermal behaviour of a battery on liquid cooling systems using standard system components. By combining a virtual battery model with a physical system, the thermal behaviour of a real battery pack is accurately reproduced. This cost-effective, safety-compliant approach enhances the development of efficient thermal management systems for BEVs. The Hardware In the Loop (HIL) platform was developed with a PXI from National Instruments and a solid-state resistance of 1 kW, while a 4 kWh battery pack prototype refrigerated with a cold plate was used for validation.
{"title":"Battery heat flow HIL for cooling system testing and optimization⁎","authors":"Benjamín Pla , Pau Bares , Andre Aronis , Victor Tomanik","doi":"10.1016/j.ifacol.2025.07.104","DOIUrl":"10.1016/j.ifacol.2025.07.104","url":null,"abstract":"<div><div>The rapid adoption of Battery Electric Vehicles (BEVs) has been driven by growing environmental awareness and advancements in energy storage technologies. However, lithium-ion cells, central to BEVs, are highly sensitive to temperature variations, requiring effective thermal management to prevent degradation, ensure safety, and optimize performance. This work presents a novel method to replicate the thermal behaviour of a battery on liquid cooling systems using standard system components. By combining a virtual battery model with a physical system, the thermal behaviour of a real battery pack is accurately reproduced. This cost-effective, safety-compliant approach enhances the development of efficient thermal management systems for BEVs. The Hardware In the Loop (HIL) platform was developed with a PXI from National Instruments and a solid-state resistance of 1 kW, while a 4 kWh battery pack prototype refrigerated with a cold plate was used for validation.</div></div>","PeriodicalId":37894,"journal":{"name":"IFAC-PapersOnLine","volume":"59 5","pages":"Pages 193-198"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144779723","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper, we propose an optimization framework for the powertrain design of a two-wheel-driven electric superbike, minimizing energy consumption. Specifically, we jointly optimize the force distribution between the wheels with the gear ratio, and rear motor and battery sizing while explicitly considering vehicle dynamics and performance constraints. First, we present an energy consumption model of the vehicle, including a scalable model of the electric machine based on data from the industry, accounting for iron, copper, and mechanical losses. Then, we analyze the propulsive blending strategy to distribute the required power to the wheels while considering adherence limits. Finally, we demonstrate the effectiveness of our approach by analyzing the design of a superbike, based on regulatory driving cycles and a custom high-performance circuit by comparing the force distribution approaches. The results underline the significance of joint optimization of powertrain components and propulsive bias, achieving a reduction of up to 22.36% in energy consumption for the Sport high-performance driving cycle.
{"title":"Two-wheel-driven Electric Superbike Powertrain Optimization","authors":"Adelmo Niccolai , Maurizio Clemente , Theo Hofman , Niccolò Baldanzini","doi":"10.1016/j.ifacol.2025.07.105","DOIUrl":"10.1016/j.ifacol.2025.07.105","url":null,"abstract":"<div><div>In this paper, we propose an optimization framework for the powertrain design of a two-wheel-driven electric superbike, minimizing energy consumption. Specifically, we jointly optimize the force distribution between the wheels with the gear ratio, and rear motor and battery sizing while explicitly considering vehicle dynamics and performance constraints. First, we present an energy consumption model of the vehicle, including a scalable model of the electric machine based on data from the industry, accounting for iron, copper, and mechanical losses. Then, we analyze the propulsive blending strategy to distribute the required power to the wheels while considering adherence limits. Finally, we demonstrate the effectiveness of our approach by analyzing the design of a superbike, based on regulatory driving cycles and a custom high-performance circuit by comparing the force distribution approaches. The results underline the significance of joint optimization of powertrain components and propulsive bias, achieving a reduction of up to 22.36% in energy consumption for the Sport high-performance driving cycle.</div></div>","PeriodicalId":37894,"journal":{"name":"IFAC-PapersOnLine","volume":"59 5","pages":"Pages 199-204"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144779724","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-01Epub Date: 2025-08-06DOI: 10.1016/j.ifacol.2025.07.077
Svante Johansson , Daniel Jung , Christofer Sundström
The electrification of commercial heavy-duty long-haul transport to battery electric vehicles (BEVs) is projected to be the dominant technology for future transport, but it is limited by short range and long charging time. This study develops a method to optimize transport with a single BEV to be cost-effective. It formulates an optimal plan for routing, charging, speed control, and resting periods to minimize the economic cost of operation. The plan considers constraints such as customer demand, road and charging networks, vehicle limitations, time windows, and Hours of Service regulations. It is shown that the optimal plan frequently operate near empty battery making detailed energy modeling critical, and that the strategy varies significantly depending on constraints at the final destination. The vehicle can be operated to save costs, through depot charging and energy efficient speed control, or increase its utilization, through fast charging. It is proposed that for BEVs, fleet coordination will benefit from close interaction with the day-to-day operation of single vehicles.
{"title":"Cost-Effective Routing of a Single Heavy-Duty Battery Electric Truck","authors":"Svante Johansson , Daniel Jung , Christofer Sundström","doi":"10.1016/j.ifacol.2025.07.077","DOIUrl":"10.1016/j.ifacol.2025.07.077","url":null,"abstract":"<div><div>The electrification of commercial heavy-duty long-haul transport to battery electric vehicles (BEVs) is projected to be the dominant technology for future transport, but it is limited by short range and long charging time. This study develops a method to optimize transport with a single BEV to be cost-effective. It formulates an optimal plan for routing, charging, speed control, and resting periods to minimize the economic cost of operation. The plan considers constraints such as customer demand, road and charging networks, vehicle limitations, time windows, and Hours of Service regulations. It is shown that the optimal plan frequently operate near empty battery making detailed energy modeling critical, and that the strategy varies significantly depending on constraints at the final destination. The vehicle can be operated to save costs, through depot charging and energy efficient speed control, or increase its utilization, through fast charging. It is proposed that for BEVs, fleet coordination will benefit from close interaction with the day-to-day operation of single vehicles.</div></div>","PeriodicalId":37894,"journal":{"name":"IFAC-PapersOnLine","volume":"59 5","pages":"Pages 31-36"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144779828","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-01Epub Date: 2025-08-06DOI: 10.1016/j.ifacol.2025.07.093
Foglia A. , Cervone D. , Frasci E. , Arsie I. , Pianese C. , Polverino P.
Polyoxymethylene dimethyl ethers (OMEx) represent a concrete solution as drop-in fuels in the context of lengthening the usage of conventional compression ignition engines, whose high efficiency and power density still make them the preferred solution for long-haul transportation. The chemical structure of these e-fuels ensures a significant reduction in soot emissions, while their enhanced combustion efficiency leads to many advantages in terms of NOx. The following study focuses on the development of a one-dimensional model for the design and optimization of control strategies with the objective of reducing the energetic drawback resulting from the introduction of OMEx in blends with Diesel. The methodology is concerned with the initial development and validation of the combustion model that is employed to simulate the performance of conventional Diesel engines. The calibration procedure and the identification of model parameters are executed using the software GT-Suite, with consideration given to different operating points across the engine map. Subsequently, an assessment of the emission reduction and optimization control strategies for Diesel/OMEx blends is conducted.
{"title":"Model based combustion control optimization of compression ignition engine fuelled with Diesel/OMEx blends","authors":"Foglia A. , Cervone D. , Frasci E. , Arsie I. , Pianese C. , Polverino P.","doi":"10.1016/j.ifacol.2025.07.093","DOIUrl":"10.1016/j.ifacol.2025.07.093","url":null,"abstract":"<div><div>Polyoxymethylene dimethyl ethers (OMEx) represent a concrete solution as drop-in fuels in the context of lengthening the usage of conventional compression ignition engines, whose high efficiency and power density still make them the preferred solution for long-haul transportation. The chemical structure of these e-fuels ensures a significant reduction in soot emissions, while their enhanced combustion efficiency leads to many advantages in terms of NOx. The following study focuses on the development of a one-dimensional model for the design and optimization of control strategies with the objective of reducing the energetic drawback resulting from the introduction of OMEx in blends with Diesel. The methodology is concerned with the initial development and validation of the combustion model that is employed to simulate the performance of conventional Diesel engines. The calibration procedure and the identification of model parameters are executed using the software GT-Suite, with consideration given to different operating points across the engine map. Subsequently, an assessment of the emission reduction and optimization control strategies for Diesel/OMEx blends is conducted.</div></div>","PeriodicalId":37894,"journal":{"name":"IFAC-PapersOnLine","volume":"59 5","pages":"Pages 127-132"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144779873","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-01Epub Date: 2025-08-06DOI: 10.1016/j.ifacol.2025.07.095
Alvin Barbier , José Miguel Salavert , Carlos E. Palau , Carlos Guardiola
This paper reflects on a concept that leverages diverse sensor configurations across a fleet of connected vehicles to enhance their emissions monitoring and diagnostics. In this vision, the vehicles of a same family are equipped with different sensor layouts and grades, and share data to support the monitoring of the entire feet. Multiple applications within this framework are outlined, and a specific use case consisting in predicting the emissions during the light-off of the tailpipe NOx sensor with artificial neural networks is discussed, demonstrating the benefits of the proposed architecture.
{"title":"Predicting NOx emissions during sensor light-off by leveraging sensor layout diversity in connected fleets⁎","authors":"Alvin Barbier , José Miguel Salavert , Carlos E. Palau , Carlos Guardiola","doi":"10.1016/j.ifacol.2025.07.095","DOIUrl":"10.1016/j.ifacol.2025.07.095","url":null,"abstract":"<div><div>This paper reflects on a concept that leverages diverse sensor configurations across a fleet of connected vehicles to enhance their emissions monitoring and diagnostics. In this vision, the vehicles of a same family are equipped with different sensor layouts and grades, and share data to support the monitoring of the entire feet. Multiple applications within this framework are outlined, and a specific use case consisting in predicting the emissions during the light-off of the tailpipe NOx sensor with artificial neural networks is discussed, demonstrating the benefits of the proposed architecture.</div></div>","PeriodicalId":37894,"journal":{"name":"IFAC-PapersOnLine","volume":"59 5","pages":"Pages 139-144"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144779875","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Autonomous driving has expanded across various domains, with advancements in urban robo-taxis, autonomous delivery vehicles, agricultural applications, and racing competitions. However, autonomous technology for two-wheeled vehicles remains under-explored, with limited literature and industrial demonstrations. Despite motorcycles already feature basic autonomous components like cruise control, traction control, and anti-lock braking systems (ABS), full autonomy demands integrated control of front braking pressure and rear regenerative torque.
This work addresses the torque allocation problem inside the longitudinal dynamics control of an autonomous motorcycle, which is under development at Politecnico di Milano from a commercial fully-electric Energica Eva Ribelle. In particular, a complementary filter-based dynamic allocation strategy is proposed to distribute braking forces effectively, considering actuator limits. After a simulation-based tuning to handle the trade-off between braking distance and vertical load transfer variations on the wheels, an experimental validation has been carried out on a test track. Experimental results confirmed the effectiveness of the proposed approach.
随着城市机器人出租车、自动送货车辆、农业应用和赛车比赛的进步，自动驾驶已经扩展到各个领域。然而，两轮车辆的自动驾驶技术仍未得到充分探索，文献和工业示范都很有限。尽管摩托车已经具备了巡航控制、牵引力控制和防抱死制动系统（ABS）等基本的自动驾驶组件，但完全自动驾驶还需要综合控制前制动压力和后再生扭矩。这项工作解决了一辆自动驾驶摩托车纵向动力学控制中的扭矩分配问题，该摩托车正在米兰理工大学（Politecnico di Milano）由商用全电动Energica Eva Ribelle开发。特别提出了一种基于互补滤波器的动态分配策略，在考虑致动器限制的情况下，有效地分配制动力。在进行了基于仿真的调整以处理制动距离和车轮垂直载荷传递变化之间的权衡之后，在测试轨道上进行了实验验证。实验结果证实了该方法的有效性。
{"title":"Design and experimental validation of a filter-based allocation strategy for the longitudinal dynamics control in an autonomous motorcycle","authors":"Stefano Radrizzani, Claudio Dallapè, Giulio Panzani","doi":"10.1016/j.ifacol.2025.07.098","DOIUrl":"10.1016/j.ifacol.2025.07.098","url":null,"abstract":"<div><div>Autonomous driving has expanded across various domains, with advancements in urban robo-taxis, autonomous delivery vehicles, agricultural applications, and racing competitions. However, autonomous technology for two-wheeled vehicles remains under-explored, with limited literature and industrial demonstrations. Despite motorcycles already feature basic autonomous components like cruise control, traction control, and anti-lock braking systems (ABS), full autonomy demands integrated control of front braking pressure and rear regenerative torque.</div><div>This work addresses the torque allocation problem inside the longitudinal dynamics control of an autonomous motorcycle, which is under development at Politecnico di Milano from a commercial fully-electric Energica <em>Eva Ribelle</em>. In particular, a complementary filter-based dynamic allocation strategy is proposed to distribute braking forces effectively, considering actuator limits. After a simulation-based tuning to handle the trade-off between braking distance and vertical load transfer variations on the wheels, an experimental validation has been carried out on a test track. Experimental results confirmed the effectiveness of the proposed approach.</div></div>","PeriodicalId":37894,"journal":{"name":"IFAC-PapersOnLine","volume":"59 5","pages":"Pages 157-162"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144779878","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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