Browse Topic: Engine cooling systems
The present work demonstrates a Fluid-Structure Interaction (FSI) based methodology that couples a Finite Volume Method (FVM) and Finite Element Method (FEM) based tools to estimate air guide deformation, thereby predicting accurate aerothermal performance. The method starts with a digital assembly step where the assembly shape and the induced stress due to assembly is predicted. A full vehicle Aerodynamic simulation is performed to extract the surface pressure on the air guide which is then used to estimate the extent of deformation of the air guides. Based on the extent a subsequent Aerodynamic simulation may be carried out to predict thermal efficiency. Comparison against pressure data and deflection data extracted from the wind tunnel experiments of vehicles has shown reasonable match demonstrating the accuracy and usefulness of the method.
This paper presents Nexifi11D, a simulation-driven, real-time Digital Twin framework that models and demonstrates eleven critical dimensions of a futuristic manufacturing ecosystem. Developed using Unity for 3D simulation, Python for orchestration and AI inference, Prometheus for real-time metric capture, and Grafana for dynamic visualization, the system functions both as a live testbed and a scalable industrial prototype. To handle the complexity of real-world manufacturing data, the current model uses simulation to emulate dynamic shopfloor scenarios; however, it is architected for direct integration with physical assets via industry-standard edge protocols such as MQTT, OPC UA, and RESTful APIs. This enables seamless bi-directional data flow between the factory floor and the digital environment. Nexifi11D implements 3D spatial modeling of multi-type motor flow across machines and conveyors; 4D machine state transitions (idle, processing, waiting, downtime); 5D operational cost
In the evolving landscape of energy efficiency and sustainability, understanding machine behavior in real-world operating conditions is essential. This solution introduces a data-driven Energy Management Dashboard designed to analyze and report critical machine parameters by leveraging LFI (Leverage Fleet Intelligence) and LFI Data (Local Field Intelligence Data). The tool serves as a robust solution for engineering and operations teams to gain actionable insights into machine performance and exposure. By tracking key parameters—such as engine fan speed, coolant temperature, and machine speed—across a fleet of machines (with support for over 1100 unique signals), the solution enables real-time monitoring and historical analysis. It helps identify when parameters go outside their specified limits and assesses the resulting impact on overall machine performance. The core functionality includes: Monitoring machine operating conditions under real field environments. Correlating parameter
A cold start occurs when the engine is cranked after being off for a long time, enough for its temperature to drop down to the cold ambient levels. Cold start in an engine is a critical phase as it is characterized by elevated emissions. During a cold start, exhaust components such as catalytic converter do not operate in its optimal temperature zone leading to reduced efficiency in emission control. New regulations for engine emissions are becoming stringent for this condition, hence it is important to accurately determine cold start condition in an engine to optimize the emissions control strategy. Accurate engine off time calculation plays a crucial role in cold start detection, emissions control and On-Board Diagnostics (OBD-II) decision making. This engine off time if greater than 6 hours indicates one of the conditions to confirm a cold start. Other conditions such as Ambient temperature and coolant temperature along with the engine off time confirms a cold start. This paper
Noise generated by a vehicle’s HVAC (Heating, Ventilation, and Air Conditioning) system can significantly affect passenger comfort and the overall driving experience. One of the main causes of this noise is resonance, which happens when the operating speed of rotating parts, such as fans or compressors, matches the natural frequency of the ducts or housing. This leads to unwanted noise inside the cabin. A Campbell diagram provides a systematic approach to identifying and analyzing resonance issues. By plotting natural frequencies of system components against their operating speeds, Test engineers can determine the specific points where resonance occurs. Once these points are known, design changes can be made to avoid them—for example, adjusting the blower speed, modifying duct stiffness, or adding damping materials such as foam. In our study, resonance was observed in the HVAC duct at a specific blower speed on the Campbell diagram. To address this, we opted to optimize the duct design
In automotive systems, efficient thermal management is essential for refining vehicle performance, enhancing passenger comfort, and reducing MAC Power Consumption. The performance of an air conditioning system is linked to the performance of its condenser, which in turn depends on critical parameters such as the opening area, radiator fan ability and shroud design sealing. The opening area decides the airflow rate through the condenser, directly affecting the heat exchange efficiency. A larger opening area typically allows for greater airflow, enhancing the condenser's ability to dissipate heat. The shroud, which guides the airflow through the condenser, plays a vital role in minimizing warm air recirculation. An optimally designed shroud can significantly improve the condenser's thermal performance by directing the airflow more effectively. Higher fan capacity can increase the airflow through the condenser, improving heat transfer rates. However, it is essential to balance fan
Thermal management is critical for modern vehicles, particularly for Zero Emission Vehicles (ZEVs), where maintaining optimal temperature ranges directly influences thermal system efficiency and vehicle range. Accurate prediction of underhood airflow behavior is essential for effective thermal management and also to estimate overall energy consumption by cooling system, with air-side dynamics playing a pivotal role in heat transfer over the heat exchangers of cooling package. Simulation tools like GT-Suite are indispensable for this purpose, enabling engineers to evaluate complex thermal interactions without the cost and time constraints of extensive physical testing. While 3D Computational Fluid Dynamics (CFD) models offer detailed insights into flow characteristics, they are computationally expensive and time consuming. In contrast, 1D models provide faster simulation times, making them ideal for system-level analysis and iterative design processes. However, 1D models inherently lack
Manufacturers of fans/propellers using hydraulically-actuated pitch control claim energy efficiency gains up to 75% over fixed-pitch solutions. Unfortunately, the added cost, weight, reliability and maintenance considerations of hydraulic solutions has limited the introduction of pitch control for small-to-medium fans and propellers leaving a large market unserved by the efficiency gains associated with changing the pitch of a blade when the blade shaft’s speed changes. Pilot Systems International and Cool Mechatronics are developing an electromagnetically controlled pitch (EMCP) fan/propeller that will produce a new pareto optimal in size, weight, power, cost and cooling (SWaP-C2). The technology will substantially improve the efficiency of military ground vehicle cooling fans which is typically the third greatest power draw (~20kW)1 in the entire vehicle and provide critical performance improvements during silent watch. It will be a key enabler for the electrification of aircraft.
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