Browse Topic: Vehicle performance
SBW(Steer-by-wire) is a steering system that transmits the driver’s request and gives feedback to the driver through electrical signals. This system eliminates the mechanical connection of the traditional steering system, and can realize the decoupling of the steering wheel and the road wheel. In addition, this system has a perfect torque feedback system, which can accurately and delicately feedback the road surface information to the driver. However, vehicle driving deviation is one of the most common failure modes affecting vehicle performance in the automotive aftermarket, this failure mode can exacerbates tire wear, reducing their life cycle, at the same time, the driver must apply a counter torque to the steering wheel for a long time to maintain straight-line travel during driving. This increases the driver’s operational burden and poses safety hazards to the vehicle’s operation. Based on the steer-by-wire system and vehicle driving deviation characteristics, this paper proposes
Spot welds are integral to automotive body construction, influencing vehicle performance and durability. Spot welding ensures structural integrity by creating strong bonds between metal sheets, crucial for maintaining vehicle safety and performance. It is highly compatible with automation, allowing for streamlined production processes and increased efficiency in automotive assembly lines. The number and distribution of spot welds directly impact the vehicle's ability to withstand various loads and stresses, including impacts, vibrations, and torsion. Manufacturers adhere to strict quality control standards to ensure the integrity of spot welds in automotive production. Monitoring spot weld count and weld quality during manufacturing processes through advanced inspection techniques such as Image processing by YOLOv8 helps identify the number of spots and quality that could compromise safety. Automating quality control processes is paramount, and machine vision offers a promising
Clutch wear is a significant factor affecting vehicle performance and maintenance costs, and understanding its dynamics is crucial for original equipment manufacturers (OEMs) to enhance product reliability and customer satisfaction. It is important to predict clutch wear to enable customers to understand the condition of their clutch and the remaining clutch life, to avoid sudden vehicle breakdowns. This paper explains the approach of measuring the clutch wear profile on an actual vehicle and simulating the same conditions on a powertrain test bench, with the establishment of a correlation in clutch wear profiles
Dynamic Vehicle mass is one of the most critical parameters in automotive controls such as battery management, transmission shift scheduling, distance-to-empty predictions and most importantly, various active and passive safety systems. This work aims to find out dynamic Vehicle mass for Electric Vehicles in real time transient driving conditions. The work proposes a real-time approach in finding Dynamic vehicle mass where accumulated Energy based vehicle performance, an improvement to the vehicle dynamics equation, has been employed for consistent and accurate results. Factors affecting vehicle mass such as road grade, dynamic friction coefficient, driving pattern, wheel slip etc. have been considered for model optimization. Here recursive Bayesian state estimator has been used for finding vehicle mass as a constant state variable while time varying forgetting factors are used to nullify the impact of major losses. Algorithm is auto tuned using Machine Learning techniques to first
ABSTRACT A retrofittable intelligent vehicle performance and fuel economy maximization system would have widespread application to military tactical and non-tactical ground vehicles as well as commercial vehicles. Barron Associates, Inc. and Southwest Research Institute (SwRI) recently conducted a research effort in collaboration with the U.S. Army RDECOM to demonstrate the feasibility of a Fuel Usage Monitor and Economizer (FUME) – an open architecture vehicle monitoring and fuel efficiency optimization system. FUME features two primary components: (1) vehicle and engine health monitoring and (2) real-time operational guidance to maximize fuel efficiency and extend equipment life given the current operating conditions. Key underlying FUME technologies include mathematical modeling of dynamic systems, real-time adaptive parameter estimation, model-based diagnostics, and intelligent usage monitoring. The research included demonstration of the underlying FUME technologies applied to a
ABSTRACT Seasonality plays a key role in altering the terrain of many military operating environments. Since seasonality has such a large impact on the terrain, it needs to be properly accounted for in vehicle dynamics models. This work outlines a variety of static and dynamic seasonal terrain conditions and their impacts on vehicle mobility in an austere region of Europe. Overall the vehicles performed the best in the dry season condition. The thaw season condition had the most drastic impact on mobility with all but the heavy tracked vehicle being almost completely NOGO in the region. Overall, the heavy tracked vehicle had the best performance in all terrain conditions. These results highlight the importance of incorporating seasonal impacts on terrain into NRMM or any vehicle dynamics model. Future work will focus on collecting more data to improve the empirical relationships between vehicles and seasonal terrain conditions, thereby allowing for more accurate speed predictions
Summary This paper discusses the latest techniques in vehicle modeling and simulation to support ground vehicle performance and fuel economy studies, enable system design optimization, and facilitate detailed control system design. The Autonomie software package, developed at Argonne National Laboratory, is described with emphasis on its capabilities to support Model-in-the-Loop, Software-in-the-Loop (SIL), Component-in-the-Loop (CIL), and Hardware-in-the-Loop simulations. Autonomie supports Model-Based Systems Engineering, which is growing in use as ground vehicles become more sophisticated and complex, with many more subsystems interacting within the vehicle and the environmental conditions in which the vehicles operate becoming more challenging and varied. With the advent of hybrid powertrains, the additional dimension of vehicle architecture has become one of the design variables that must be considered. This complexity results in the need for a simulation tool that is capable of
ABSTRACT Durability analysis as applied to high mobility off-road ground vehicles involves simulating the vehicle on rough terrains and cascading the loads throughout the structure to support the verification of various components. For components within the hull structure, the rigid body accelerations of the hull are transformed to the component location producing a prescribed g-load time history. This modeling method works extremely well for items which are bolted in place but is inappropriate for stowage systems such as boxes and shelves where cargo can experience intermittent contact and impacts. One solution is to create a dynamic contact nonlinear finite element model of the stowage solution with supported cargo and subject them to the same acceleration profile. This approach effectively resolves the stresses needed to perform fatigue evaluations but is a computationally and labor intensive process. The resources required for single design point verification cannot be justified
ABSTRACT Model based design techniques are being used increasingly to predict vehicle performance before building prototype hardware. Tools like ADAMS and Simulink enable very detailed models of suspension components to be developed so vehicle performance can be accurately predicted. In creating models of vehicle systems, often there is a question about how much component detail or model fidelity is required to accurately model system performance. This paper addresses this question for modeling shock absorber performance by comparing a low fidelity and high fidelity shock absorber model. A high fidelity and low fidelity mathematical model of a shock absorber was developed. The low fidelity shock absorber model was parameterized according to real shock absorber hardware dimensions. Shock absorber force vs. velocity curves were calculated in Simulink. The results from the low fidelity and high fidelity model were compared to shock absorber force vs. velocity test results. New vehicle
ABSTRACT A discussion on the utility of physics-based compact thermal models to guide the design, integration, operation and control of thermally sensitive vehicle components is presented. Effective component selection requires honest and accurate representation of the key performance attributes expressed by physics-based models. Parallel developments and lessons learned from the Electronics Industry on component packaging and characterization is discussed. An example application of a physics-based model driven design is presented for an Electrical Energy Dissipater design used on typical hybrid vehicles. Low fidelity models are used early in the design to support system requirements decomposition into discreet design attributes. High fidelity thermal and electromagnetic models are used to explore the design space and to optimize performance metrics. Accurate and robust reduced order thermal models are used for the continuous prognostic, diagnostic monitoring and control of the device
Items per page:
50
1 – 50 of 1417