Browse Topic: Control systems

Items (5,593)
Large-spacing truck platooning offers a balance between operational safety and fuel savings. To enhance its performance in windy environments, this study designs a control system integrating both longitudinal and lateral motions. The longitudinal control module regulates the inter-vehicle spacing within a desired range while generating a fuel-optimal torque profile by minimizing unnecessary decelerations and accelerations. The lateral control module ensures lateral stability and maintains alignment between the trucks to achieve the expected fuel savings. A two-truck platoon is simulated with a 3-sec time gap under varying wind conditions, using experimental data from the on-road cooperative truck platooning trials conducted in Canada. The control system effectively remains spacing errors within the preset safety buffer and limits lateral offsets to 0.07 m, ensuring safe and stable platooning in windy environments. Additionally, the smoother speed profiles and reduced lateral offsets
Jiang, LuoShahbakhti, Mahdi
The increasing importance of electric vehicles requires addressing challenges related to fast charging, safety, and battery range. Thermal management ensures safety, prolongs battery life, and enables extremely fast charging. In this regard, this article proposes a novel battery thermal management system (BTMS) optimization approach based on a model-free deep reinforcement learning (RL) for a battery pack of an electric vehicle under extreme fast-charging conditions considering the detailed dynamics of vehicle-level BTMS. The objective of the proposed approach seeks to minimize the battery degradation and power consumption of the underlying BTMS. In this respect, the dynamic equations of the thermal system model are constructed considering the air-conditioning refrigerant loop and indirect battery liquid cooling loop. Further, the proposed methodology is implemented on a battery pack, and the results are compared with those of model predictive control (MPC) and proportion–integral
Arjmandzadeh, ZibaHossein Abbasi, MohammadWang, HanchenZhang, JiangfengXu, Bin
The Dosing Control Unit (DCU) is a vital component of modern emission control systems, particularly in diesel engines employing Selective Catalytic Reduction technology (SCR). Its primary function is to accurately control the injection of urea or Diesel Exhaust Fluid (DEF) into the exhaust stream to reduce nitrogen oxide (NOₓ) emissions. This paper presents the architecture, operation, diagnostic features, and innovation of a newly developed DCU system. The Engine Control Unit, using real-time data from sensors monitoring parameters such as exhaust temperature, NOₓ levels, and engine load, calculates the required DEF dosage. Based on DEF dosing request, the DCU activates the AdBlue pump and air valve to deliver the precise quantity of diesel exhaust fluid needed under varying engine conditions. The proposed system adopts a master-slave configuration, with the ECU as the master and the DCU as the slave. The controller design emphasizes cost-effectiveness and simplified hardware, and
Raju, ManikandanK, SabareeswaranK K, Uthira Ramya BalaKrishnakumar, PalanichamyArumugam, ArunkumarYS, Ananthkumar
A futuristic vehicle chassis rendered in precise detail using state-of-the-art CAD software like Blender, Autodesk Alias. The chassis itself is sleek, low-slung, and aerodynamic, constructed from advanced materials such as high-strength alloys or carbon-fibre composites. Its polished, brushed-metal finish not only exudes performance but also emphasizes the refined form and engineered details. Underneath this visually captivating structure, a sophisticated system of self-hydraulic jacks is seamlessly integrated. These jacks are situated adjacent to the four shock absorber mounts. These jacks are designed to lift the chassis specifically at the tyre areas, and the total vehicle, ensuring that underbody maintenance is efficient and that, in critical situations, vital adjustments or emergency lifts can be performed quickly and safely. The design also incorporates an intuitive control system where the necessary buttons are strategically placed to optimize driver convenience. Whether
Gogula, Venkateswarlu
Tippers transporting loose bulk cargo during prolonged descents are subject to two critical operational challenges: cargo displacement and rear axle lifting. Uncontrolled cargo movement, often involving loose aggregates or soil, arises due to gravitational forces and insufficient restraint systems. This phenomenon can lead to cabin damage, loss of control, and hazardous discharge of materials onto roadways. Simultaneously, load imbalances during descent can cause rear axle lift, increasing stress on the front steering axle, resulting in tire slippage and compromised maneuverability. This study proposes a dynamic control strategy that adjusts the tipper lift angle in real time to align with the descent angle of the road. By synchronizing the trailer bed angle with the slope of the terrain, the system minimizes cargo instability, maintains rear axle contact, and enhances braking performance, including engine and exhaust braking systems. Computational modelling is employed to assess the
Vijeth, AbhishekBhosle, Devidas AshokCherian, RoshniDash, Prasanjita
Manufacturers need pragmatic guidance when choosing network protocols that must balance responsiveness, high data throughput, and long-term maintainability. This paper presents a step-by-step, criteria-driven framework that scores protocols on six practical dimensions, real-time behavior, bandwidth, interoperability, security, IIoT readiness, and legacy support and demonstrates the approach on both greenfield and brownfield scenarios. By combining vendor specifications, peer-reviewed studies, and field experience, the framework delivers transparent, weighted rankings designed to help engineers make defensible deployment choices. This paper explores how network protocols can be mapped to different layers of the automation pyramid, ranging from field-level communication to enterprise-level. For example, Profinet is shown to be highly effective for time-critical applications such as robotic assembly and motion control due to its deterministic, real-time ethernet capabilities. Meanwhile
Tarapure, Prasad
Tillage, a fundamental agricultural practice involving soil preparation for planting, has traditionally relied on mechanical implements with limited real-time data collection or adjustment capabilities. The lack of real-time data and implement statistics results in fleet managers struggling to track performance, driver behavior, and operational efficiency of the implements. Lack of data on vehicle performance can result in unexpected breakdowns and higher maintenance costs, ensuring compliance with regulations is challenging without proper data tracking, potentially leading to fines and legal issues. Bluetooth-enabled mechanical implements for tillage operations represent an emerging frontier in precision agriculture, combining traditional soil preparation techniques with modern wireless technology. Implement mounted battery powered BLE (Bluetooth Low Energy) modules operated by solar panel based rechargeable batteries to power microcontroller. When Implement is operational turns
Kaniche, OnkarRajurkar, KartikGokhale, SourabhaVadnere, Mohan
This paper studies an important industrial controls engineering problem statement on mitigating vibrations in a mechanical boom structure for an off-highway agricultural vehicle. The work discusses the implementation of an active force control concept to efficiently dampen out vibrations in a boom. Through rigorous simulation comparison with respect to an existing PID mechanism, the efficacy of the AFC is demonstrated. A notable reduction of 60 % to 70 % in the boom vibrations was observed.
Patil, BhagyeshBawankar, Shubham
In motorcycle racing and other competitions, there is a technique to intentionally slide the rear wheel to make turns more quickly. While this technique is effective for high-speed riding, it is difficult to execute and carries risks such as falling. Therefore, an anti-sideslip control system that suppresses unintended or excessive sideslip is needed to ensure safe, natural, and smooth turning. In anti-sideslip control, the slip angle is usually used as a control parameter. However, for motorcycles, it is necessary to know the absolute direction of the vehicle's movement. To determine this, GPS or optical sensors are required, but using such sensors for driving is costly and may not provide accurate measurements due to contamination or other environmental factors, making it impractical. Therefore, an anti-sideslip control system was developed by calculating another parameter that indicates the characteristics of the slip angle, without measuring the slip angle itself, thus eliminating
Nakano, KyosukeKawai, KazunoriTakeuchi, Michinori
To mitigate greenhouse emissions such as carbon monoxide (CO), carbon dioxides (CO2), oxide of nitrogen (NOx) and particulate matter reduction Government of India implemented Bharat Stage VI (BS-VI) norms from year 2020. Moving to more stringent emission norms poses challenges for automakers in several ways such as meeting exhaust emissions, on board diagnostic, drivers’ inducement, and particulate filter monitoring on vehicle. It is imperative to upgrade engine management system for on-board diagnostics (OBD) that refers to a vehicles self-diagnostic and reporting ability. On board diagnostics systems enables owner of vehicle to gain access of the various vehicle sub-systems. OBD-II standards were made more rigid, requiring the malfunction indicator lamp (MIL) to be activated if emission-related components fail. Also, vehicle emissions carbon monoxide (CO), oxide of nitrogen (NOx) and particulate matter not to exceed OBD thresholds. Consequently, the use of specific oxide of nitrogen
Jagtap, PranjalSyed, KaleemuddinChaudhari, SandipKhairnar, GirishBhoite, VikramReddy, Kameswar
Widespread adoption of electric vehicles (EVs) is hindered by "range anxiety," a major concern for consumers. A primary contributor to this issue is the significant energy consumption of the Heating, Ventilation, and Air Conditioning (HVAC) system, which can account for 15-40% of a vehicle's total energy demand, directly reducing its practical driving range. Using the 1D simulation tool GT-SUITE, this research provides a comparative analysis of two distinct HVAC architectures: a conventional air-cooled condenser (ACC) and a proposed liquid-cooled condenser (LCC). The performance of both hardware systems was evaluated under two control strategies a Proportional-Integral (PI) controller and a basic On/Off controller—to identify the optimal configuration. The results advocate that optimizing the system's architecture and control logic yields a substantial improvement in the Coefficient of Performance (COP) ranging from 47% to 128% compared to the baseline ACC/On-Off configuration, with a
T R, RakshithYadav, Ankit
Cabin air quality plays a crucial role in ensuring passenger comfort, health and driving experience. There have been growing concerns over poor cabin air quality resulting from multiple factors, including infiltration of external pollutants such as particulate matter, volatile organic compounds, emissions from vehicle interior materials, microbial contamination and inadequate ventilation. Therefore, maintaining optimal air quality inside vehicle cabin has become a critical aspect of vehicle climate control systems. Additionally, high humidity levels inside the cabin contribute to mold growth and fogging of windows, further compromising both air quality and visibility. This review explores such factors contributing to poor cabin air quality, where the severity of these issues ranges from mild discomfort and allergic reactions to long-term respiratory ailments. To mitigate these challenges, automotive manufacturers and researchers have implemented various air purification and filtration
Sharma, Shrutika
This study demonstrates the application of the T-Matrix, a Total Quality Management (TQM) tool to improve thermal comfort in automotive climate control systems. Focusing on the commonly reported customer issue of insufficient cabin cooling, particularly relevant in hot and congested Indian driving conditions, the research systematically investigates 36 failure modes identified across the product lifecycle, from early design through production and post-sale customer usage. Root causes are first categorized using an Ishikawa diagram and then mapped using the T-Matrix across three critical stages: problem creation, expected detection, and actual detection. This integrated approach reveals process blind spots where existing validation and inspection systems fail to catch known risks, particularly in rear-seat airflow performance and component variability from suppliers. By applying this TQM methodology, the study identifies targeted improvement actions such as improved thermal targets
Jaiswara, PrashantKulkarni, ShridharDeshmukh, GaneshNayakawadi, UttamJoshi, GauravShah, GeetJaybhay, Sambhaji
Single-zone cabin climate control systems have been standard for decades in passenger cars. Looking at the technology trend, which is transitioning from single-zone to multi-zone automatic control systems, it is now possible to provide zonal comfort tailored to the individual requirements of each passenger. In current single-zone climate control systems, maintaining the cabin temperature as stated by the passenger has been straightforward and can be achieved with slight calibration efforts using the present set of parameters and sensors until now. In this work, a multi-zone climate system highlighting the importance of individual calibration parameters in improving cabin comfort when transitioning from a single-zone to a multi-zone climate control system is proposed. As multi-zone climate systems are based on passenger set temperature requests for individual zonal comfort, appropriate controller fine-tuning is challenging when an input is taken from various sensed parameters, including
Varma, MohitSwarnkar, Sumit KumarBHOSALE, KRISHNAPatil, PrashantSardesai, Suresh
Modern battery management systems, as part of Battery Digital Twin, include cloud-based predictive analytics algorithms. These algorithms predicts critical parameters like Thermal runaway events, state of health (SOH), state of charge (SOC), remaining useful life (RUL), etc. However, relying only on cloud-based computations adds significant latency to time-sensitive procedures such as thermal runaway monitoring. This is a very critical and safety function and delay is not acceptable, but automobiles operate in various areas throughout the intended path of travel, internet connectivity varies, resulting in a delay in data delivery to the cloud and similarly delay in return of the detected warning to the driver back in the vehicle. As a result, the inherent lag in data transfer between the cloud and vehicles challenges the present deployment of cloud-based real-time monitoring solutions. This study proposes application of Federated Learning and applying to a thermal runaway model in low
Sarkar, Prasanta
During air conditioning operation in automobiles (ICE and EVs), cabin air is predominantly recirculated to reduce heating and cooling loads of occupant space. However, prolonged recirculation of air leads to deteriorated cabin air quality. Simply introducing fresh air to improve air quality is inefficient, as external air conditions are unpredictable and may negatively affect energy consumption as well as cabin interior air quality. Moreover, even in recirculation mode under low ambient conditions where de-humidified air is available outside, energy usage increases due to the dual operation of the electric compressor (e-Compressor) and the Positive Temperature Coefficient (PTC) heater especially in case of Electric Vehicle. In this dual-mode scenario, the e-Compressor maintains a low evaporator temperature for effective air dehumidification, while the PTC heater supplies sensible heating to achieve the desired cabin comfort. In case of ICE vehicle the heater is coolant based and free
Kumar, SunnyVenu, SantoshRaj, ShivamKhan, Farhan
In both Internal Combustion Engine Vehicles (ICEVs) and Electric Vehicles (EVs), the refrigerant charge is essential for efficient climate control and energy consumption. An accurate refrigerant charge allows the system to regulate cabin temperature effectively and optimizing energy use. In ICEVs, this prevents the wastage of engine power. In EVs, it preserves battery life by minimizing energy drain by the climate control systems. Undercharging or Overcharging has adverse effects on the Heat Ventilation Air-Conditioning (HVAC) systems and the energy usage associated with it. Undercharging leads to poor cabin cooling which reduces heat absorption by refrigerant whereas overcharging leads to higher energy consumption by compressor, and potential damage to components, which can lead to wear, leaks, and system failures. Hence it is crucial to use optimum refrigerant charge quantity in Mobile Air-Conditioning (MAC) system both in ICEVs and EVs. Previous work on refrigerant charge
Shah, GeetJaiswara, PrashantKulkarni, ShridharJaybhay, Sambhajivangala, Sai krishnaM, Chandru
Four-wheel independent steering four-wheel independent drive electric vehicles have an independent steering motor and an independent driving motor for each wheel, for a total of eight motors. About 28 works in this emerging field have shown path-tracking control algorithms for these vehicles, 18 of them explicitly or implicitly aspire for a condition known as optimal tire usage. This article first defines this optimality condition and explains its significance. Second, this article identifies three indicators of tire usage that aid in assessing the existing algorithms. Third, this article performs block diagram examination of four of the 18 works, revealing significant commonalities across the 28 works and identifying areas for improvement in three of the four algorithms. Lastly, this article suggests motor control systems to fill these gaps. Furthermore, it employs these motor control systems in one of the four algorithms, and illustrates path-tracking and achievement of the
Kumar, DileepPotluri, Ramprasad
Trains traditionally transmit braking and mitigation commands through the air tube filling and exhausting method, which is easy to cause local large longitudinal impact. In order to meet the high-precision requirements of synchronous transmission of commands for heavy-duty trains with large groupings, this paper proposes a laser+industrial Ethernet network control system, which can meet the requirements of flexible train grouping and virtual connecting under the premise of ensuring synchronous transmission of commands for trains with large groupings. The system consists of central control unit, locomotive laser communication module, locomotive switch, mobile wireless communication terminal, security gateway, vehicle control unit, vehicle laser communication module, vehicle switch, etc. It is designed according to the three-layer architecture of vehicle-level network, train-level network and line-level network, which can realise the issuance of internal control commands and status
Meng, XiangzhenLi, ChuanhuZhu, Youlong
Heavy-duty vehicles emissions are a serious problem, and remote monitoring platforms are a key means of emission control for heavy-duty vehicles. However, the frequent occurrence of anomalies in the remote monitoring data has seriously limited the monitoring efficiency of the remote monitoring platform. Therefore, this paper takes 500 National VI heavy-duty vehicles as the research object, and proposes a whole-process data quality control system of “anomaly identification-dynamic correction-accuracy verification”. First, four types of anomaly patterns, namely, lost, invalid, outlier and mutation, are defined, and polynomial fitting, median filtering and contextual interpolation are adopted to realize differentiated correction. Second, a data accuracy validation framework based on correlation analysis was constructed. The results show that the accuracy of key parameters is significantly improved after correction, and the data fitting degree R2 is greater than 0.97. The research results
Liu, YuZhang, ChengZhang, HaoYu, HanzhengnanLi, JingyuanAn, XiaopanMa, KunqiLiang, YongkaiXu, Hang
The development of urban rail transit has diversified communication infrastructure needs, and the design of Communication-Based Train Control(CBTC) system is critical to improving passenger service quality. To ensure that all requirements are accurately communicated and traceable during the model design process, this paper conducts CBTC system modeling work based on model system engineering concepts. Requirements extraction, as a key step in system design and development, directly affects system performance, but traditional requirements extraction methods rely on manual analysis, which is time-consuming and error-prone. In this regard, this paper proposes a requirement extraction framework based on Named Entity Recognition (NER) technology, including requirement document preprocessing, key requirement extraction by BERT-BiLSTM-CRF and automated generation of requirement entries, and two sets of comparative experiments were conducted, and the results show that the model realizes the
Wan, KeyanWang, BaominWang, QingyongZhou, LujieGuan, Lin
Adaptive vehicle control systems are crucial for enhancing safety, performance, and efficiency in modern transportation, particularly as vehicles become increasingly automated and responsive to dynamic environments. This review explores the advancements in bio-inspired actuators and their potential applications in adaptive vehicle control systems. Bio-inspired actuators, which mimic natural mechanisms such as muscle movement and plant tropism, offer unique advantages such as flexibility, adaptability, and energy efficiency. The article categorizes these actuators based on their mechanisms, including shape memory alloys, dielectric elastomers, ionic polymer–metal composites, and soft pneumatic actuators. The review highlights the properties, operating principles, technical maturity, and potential applications for each mechanism in automotive systems. Additionally, it investigates current uses of these actuators in adaptive suspension, active steering, braking systems, and human–machine
Mittal, VikramShah, RajeshRoshan, Mathew
Designing the gear shift control for an automotive transmission is a complex task because it involves handling nonlinear behaviors like changes in friction between clutch plates and fluctuations in oil temperature. While deep reinforcement learning (DRL) has recently been used to reduce shift shock, most existing methods don’t account for real-world changes such as transmission aging. One major issue that becomes worse with aging is clutch judder—a type of vibration caused by wear. Traditional reinforcement learning assumes that the environment stays the same, which can lead to unstable learning when conditions change, making it hard to consistently reduce shift shock. To address this, we propose a new algorithm that adapts to aging transmissions by adjusting the discount factor—a key parameter in reinforcement learning that balances short-term and long-term rewards. Instead of keeping this factor fixed, our method starts with a lower value to ensure stable learning and gradually
Ogawa, KazukiAihara, TatsuhitoGoto, TakeruMinorikawa, Gaku
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