Steering Knuckle Research Articles

Chassis concept of the individually steerable five-link suspension: a novel approach to maximize the road wheel angle to improve vehicle agility

The Institute of Vehicle Systems Engineering at Ulm University of Applied Sciences is currently developing the autonomous concept vehicle Nimbulus-e in the strategic field “Intelligent Commercial Vehicles” with the aim of maneuvering as agilely as possible in confined spaces. To achieve high agility under the conditions mentioned, large road wheel steering angles are necessary. As part of the basic vehicle concept, the first step is to select a suitable chassis for this purpose. Conventional suspensions cannot be applied due to the mechanical connection of the tie rod to the steering knuckle limiting the road wheel angles. Therefore, the approaches published so far for individual chassis concepts with large steering angles are analyzed and evaluated for use. In this paper, the concept of a novel individually steerable five-link suspension is described. The concept includes a vehicle body mounted steering actuator connected to the chassis via a self-locking worm gear. Due to the body mounted connection of the steering actuator, it does not contribute to the unsprung mass. An analysis of the kinematic and elastokinematic properties and the achievable road wheel steering angle is presented. In the Nimbulus e concept vehicle, the individually steerable corner module is used on both the front and the rear axle. The system is driven by four wheel hub motors. This means that eight control variables are available for the vehicle.

Multi-objective topology optimization method for multi-axis random vibration based on hybrid cellular automata

Considering the lack of effective solutions for multi-axis random vibration topology optimization problems, and recognizing that multi-axis random vibration excitation is the most common loading conditions experienced by structures during their operational life, this paper proposes a multi-objective topology optimization method for multi-axis random vibration. By combining Hybrid Cellular Automata (HCA) and Analytic Hierarchy Process (AHP), this method aims to enhance the vibration resistance of structures and extend their fatigue life during the topology optimization phase. To validate the effectiveness and engineering practicality of this method, two engineering cases were designed: a cantilever beam case and an automotive steering knuckle case. Multi-objective topology optimization were conducted with objectives including mass, stiffness, and vibration intensity metric (root-mean-square stress). The two cases demonstrate that the control group's topology model exhibits weaker resistance to random vibrations and shorter fatigue life. In contrast, the validation group's topology model introduces an additional load path near the excitation point, effectively dissipating the impact of vibration excitation. This enhances the structure's vibration resistance and significantly extends its fatigue life.

Development of Automobile Aluminum/CFRP Hybrid Steering Knuckle

Abstract: The suspension system of a vehicle plays an important part in precisely controlling the stir of the wheel throughout the trip. The perpendicular and the side dynamics (lift and running) are affected by the unsprung to sprung mass rate. Lower value of this mass rate leads to enhanced performance of the auto. Light weight and low fuel consumption are the two main demands for a vehicle. To optimize the unsprung mass of the auto, the design of the control arm plate is optimized with Aluminum material, and Carbon fiber corroborated compound control arm frames are used to achieve high stiffness to weight rate. This leads to an increase in the overall power-to-freight rate of the auto which helps to deliver maximum performance to the Vehicle. The improved design obtained had achieved 45.8% reduction of mass while meeting the strength requirement

Lightweight Design and Analysis of Steering Knuckle of Formula Student Car Using Topology Optimization Method

The steering knuckle is a crucial component of student racing vehicles, designed by the Formula Society of Automotive Engineers (FSAE). Developing a lightweight (LW) vehicle that meets the requirements of the student formula car presents a challenge. This study presents a LW design of the steering knuckle using the Topology Optimization (TO) approach for the Formula Society of Automotive Engineers (FSAE) competition considering two different mass constraints (40% and 48%). Moreover, the research includes Stress–Life (SN) curves for three materials, structural steel, 4130 steel, and AISI 1020 steel, providing essential insights into the fatigue characteristics of the model. The results compare the three materials and two mass reduction levels, with steel 4130 achieving a significant mass reduction of 42.70%. Additionally, steel 4130 exhibits superior performance in weight reduction, stress, deformation, and safety aspects. The optimized design meets the criteria for strength, stiffness, and safety under various conditions. The fatigue analysis reveals that AISI 1020 and steel 4130 have superior endurance (1 × 105 and 2 × 105 cycles, respectively). This research provides significant contributions to the development of a LW, high-performance steering knuckle for student formula racing vehicles, highlighting the significance of TO and material selection in achieving optimal outcomes.

Topology Optimization of a Steering Knuckle

Steering knuckle is an important component from safety point of view since they are subjected to large amount of stresses. Hence to study the stress pattern in steering knuckle. ANSYS static structural workbench model is used. For analysis purpose basic model is prepared by picking data from available literature. For numerical analysis steering knuckle is prepared by using the software CATIA V5 and the stress analysis is done by FEM in ANSYS. Topology optimization have been performed for optimization of the volume and reduce the materials from the steering knuckle by using topology optimization module in ANSYS. Comparison between the results from post and pre-optimization will be done and discussed.

Failure Strength of Automotive Steering Knuckle Made of Metal Matrix Composite

This article presents the static performance of composite steering knuckle due to drive on an equivalent road, including different types of roughness and maneuvers. To achieve this purpose, the driving of a full-vehicle model was simulated using the multi-body dynamics (MBD) method, and the imposed loads on connection points of the steering knuckle to different components of the suspension system were extracted considering various maneuvers. Next, CATIA software was used to prepare a smooth model of the steering knuckle by employing coordinate measuring machine (CMM) data. Stress analysis was performed under the maximum value of the loading history in finite element (FE) software. Eventually, the safety factor was calculated based on some well-known criteria for static failure of the composite materials. Moreover, the optimum value of tungsten carbide as a reinforcing substance in aluminum composite was estimated to increase failure strength. The results show that an increase in tungsten carbide leads to an increase in the strength of the steering knuckle under purely axial loads (normal stress criterion) and also that an increase in this substance leads to a decrease in the strength of the part under shear loads (shear stress criterion). Therefore, based on the nature of the loads (i.e., multi-axial non-proportional random amplitude loading conditions) applied to the automotive steering knuckle due to actual conditions, this metal matrix composite (aluminum matrix and tungsten carbide as reinforcement) is not practical.

Accelerated durability evaluation of automotive components under multi-channel random loading

Accelerated durability evaluation aims to quantify the fatigue damage of automotive components in a shorter time. The quality of accelerated editing directly affects the evaluation’s efficiency and accuracy. In this paper, an index-controlled accelerated spectrum editing method is proposed, and the equivalent fatigue damage model of the component is derived. Taking an automotive steering knuckle as the verification object, the proposed accelerated editing method is evaluated from multiple perspectives. The evaluation results show that the proposed method has apparent advantages in compression efficiency, damage consistency, and retaining the frequency domain impact on the component.

Crack identification of automobile steering knuckle fluorescent penetrant inspection based on deep convolutional generative adversarial networks data enhancement

As a key safety component of automobiles, automobile steering knuckles must be subjected to strict quality control. Currently, the identification of cracks in finished products primarily relies on manual identification of fluorescent penetrant detection. Owing to the complex shape of the workpiece, the interference of the displayed image and the small sample size, the accuracy of the automatic discrimination result of the fluorescent penetrant detection image is directly reduced. Therefore, this study proposed a data augmentation method based on deep convolutional generative adversarial networks (DCGAN) for crack identification in automotive steering knuckle fluorescent penetration inspection images. An image acquisition platform was built for fluorescence penetration detection of automobile steering knuckles, and fluorescence display images of various parts of the workpiece were collected. Based on the feature analysis of the displayed image, the image was preprocessed to suppress relevant interference and extract crack candidate regions. Further, using the original crack image to train DCGAN, several crack image samples were generated, the ResNet network was trained with the expanded dataset, and the extracted candidate regions were identified. Finally, the experimental results show that the recall rate of the crack recognition method used in this paper is 95.1%, and the accuracy rate is 90.8%, which can better identify the crack defects in the fluorescent penetrant inspection image, compared with the non-generative data enhancement method.

ВЫПОЛНЕНИЕ ГЕНЕРАТИВНОГО ДИЗАЙНА И АДАПТАЦИЯ К ИЗГОТОВЛЕНИЮ ПОВОРОТНОГО КУЛАКА ЧАСТЬ II

The article describes the creation of a 3D model of the steering knuckle of the “Formula Student” class car using the SolidEdge CAD / CAE system application, named generative design. The initial data are a model of an overly strong steering knuckle, previously calculated load values for various operating modes, information about the properties of the material. In the process of optimization, technological settings are varied in order to obtain a geometry that is as suitable as possible for cutting on a three-axis milling machine with a CNC and without an additional rotary axis. The result of the generative design is used to build a model of a knuckle that can be milled with repositioning and clamped into universal fixtures such as a vise. The construction is carried out using standard solid modeling tools (lofting by sections, adding thickness, etc.). Fastening elements have been added to the part, in the form of rectangular bodies, which will need to be removed using manual cutting and grinding operations after the milling operations are completed. Additionally, holes are removed parallel to the Z axis, which can only be made after cutting the fasteners.

Comparison of some selected time-domain fatigue failure criteria dedicated for multi input random non-proportional loading conditions in industrial components

This paper presents time-domain procedure to evaluate High-Cycle Fatigue (HCF) life of industrial components with complicated geometries and subjected to multi-input random loading conditions. To this end, the authors discuss some well-known equivalent stress criteria which can consider the orientation of critical plane changes with the time in non-proportional loading conditions to estimate the time history of equivalent stress. This task is successfully accomplished by knowing time histories of local stress tensor components in a critical area of the part that is prone to failure. Next, two different categories were used to predict fatigue life of component: 1- Linear Damage Accumulation (LDA) rule by employing Rain-flow cycle counting and 2- probabilistic approach by utilizing level crossing counting method. To apply these methodologies and awareness of their challenges, a case study was performed on the automotive steering knuckle. Finally, the predicted lives were compared to experimental results, and the accuracies of different fatigue life assessment techniques were reported. The obtained results show that combination of Rain-flow cycle counting with the Liu-Zenner criterion and especially, with the Energy-based instant fatigue damage tracing proposed by Shariyat lead to the highest accuracies. However, using the probabilistic approach, we will get the response in a much shorter time compared to another category. Therefore, the choice which method to use also depends on the parameters of the research situation, and the interaction of the two factors of prediction accuracy and prediction time in the industry.

Study on failure assessment and experimental validation of automotive steering knuckle in McPherson front suspension system

The failure phenomenon of automotive components within the service life is one of the most concerning issues in the automotive industry. In this paper, the concept of deformation gradient is introduced into the CAE simulation results to obtain the critical strain of the component under large deformation conditions. Subsequently, a complete quasi-static failure prediction method combined with the Johnson-Cook criterion is proposed. In addition, considering the cyclic hardening effect of the components’ material, the subcritical plane model is improved based on the Fatemi-Socie model to make the fatigue life prediction more accurate. According to the assembly relationship of the McPherson front suspension system, the proposed method and the improved model are used to predict the failure of the steering knuckle. Finally, the predicted results are compared with the rig test results. The comparison results validate the applicability and accuracy of the proposed quasi-static failure prediction method and fatigue failure prediction model.

Stiffness/constraint effects in analytical flaw assessment. A technical note

Using the case study of a fail-safe design criterion for a steering knuckle of a commercial vehicle, the effect of stiffness/constraint on the crack driving force in the component is discussed. The problem arises when assessment procedures such as R6, BS 7910 or SINTAP/FITNET are applied in conjunction with substitute geometries for determining the model parameters K-factor and limit load (or a substitute for the latter), as it is common practice. In the example, the conservatism was so pronounced that this procedure was in fact unusable. A way out could be the finite element-based determination of the model parameters and their use in the analytical framework. This procedure is useful and effective if the finite element-based calculations are used in parameter sensitivity analyses.

Design, Analysis of Car Knuckel by using ANSYS Workbench

Abstract: Steering knuckle is an indispensable part of an automobile vehicle, integrating different subsystems like suspension, brakes and steering. Being the pivot point of the vehicle, it undergoes diverse stacking under rigorous conditions resulting in failure of the component. The objective of this paper is to perform static structural analysis on the knuckle under diverse loadings. This is achieved by designing a generic steering knuckle of a car in CATIA V5R20 and performing the finite element analysis using ANSYS Workbench 14.5. The analysis is carried out under maximum loading condition, braking and bump maneuvering.

Investigation into the Formation of Inclusions in a Steering Knuckle Casting of Low-Silicon Cast Aluminum Alloy

Investigation into the Formation of Inclusions in a Steering Knuckle Casting of Low-Silicon Cast Aluminum Alloy

Structure Optimization of Semi-Solid Die Cast Steering Knuckle and its Experiment Verification

Steering knuckles are vital functional and structural components in automotive suspension systems, requiring high strength, high ductility, and complex shapes. In this study, an aluminum alloy knuckle with the semi-solid die casting process was developed to replace the conventional steel components. This research aims to optimize product design based on both structural simulation and casting process simulation to avoid defects and to meet mechanical requirements. Furthermore, the optimal design solutions need to be verified through the filling experiments and defect analysis. The results show that the removal of support rib located in the thick area of the shock absorber mounting arm is helpful to avoid the rewelding defects in the filling frontier of the SSM melt. Besides, the position of the steering rod is of medium thickness, and two ribs from different directions come together to support that area. Rewelding defects were detected when two ribs come together. To avoid rewelding defects in local areas of steering rod position, the ribs were reduced to uniform wall thickness. Thus, the local flow state was modified and the SSM melt was reinforced shear action. Ultimately, by controlling all the processes of the SSM die casting process, the high performance of aluminum knuckle was successfully developed.

Product Re-Engineering by Topology Optimization for Forged Component

Optimization tools are used when a set of objectives is used to find the best alternative proposed design. Topology optimization adds a whole new level of process of developing creative design space. The objective of topology design is to obtain a material distribution inside a given design space that is optimum in this aspect. Material is rearranged and elements that are not necessary from an objective point of view are eliminated throughout the optimization process. For Topology optimization of the forged component which is selected from industry which is steering knuckle assembly is optimized and presented in this study. For topology optimization, platform such as 3D experience is used to simulate the part. A number of modules from 3D experience is used for FEA analysis, mesh-smoothening techniques and creating parametric geometry in terms of shape and explored in way to produce the topology geometry more functional. Functional Generative Design module is used for topology optimization. From this study overall weight reduction is achieved after using the finite element method to analyze a steering knuckle assembly and performing topology optimization. And the part is optimized in terms of shape and for further suitable manufacturing process. According to the result of this research, 64% relative weight reduction is achieved in respect to a given target is 50%. The original weight of the knuckle was 843 gm. however it has since been reduced to 513 gm. As a result, the cost of knuckle is lowered.

Repairability Evaluation of Retired Hot Forging Die Based on Matter-Element Extension Model

Hot forging die is one of the important tools for machining. Because of its bad working environment, it is prone to lose its effect. Repairing the retired hot forging die can reduce the production cost and prolong the service life of the die, which has good economic benefits. In view of the complexity and uncertainty of hot forging die repair process, and the complexity and uncertainty of hot forging die repair process, this paper constructed the evaluation indexes of technical feasibility, economic feasibility, environmental feasibility, life-span feasibility and time-effectiveness feasibility, and comprehensively uses AHP and matter-element extension model to evaluate the repairability of retired hot forging dies. The rationality of this method was verified by the repairability evaluation of the hot forging die of a retired automobile steering knuckle.

Robust design optimization under dependent random variables by a generalized polynomial chaos expansion

New computational methods are proposed for robust design optimization (RDO) of complex engineering systems subject to input random variables with arbitrary, dependent probability distributions. The methods are built on a generalized polynomial chaos expansion (GPCE) for determining the second-moment statistics of a general output function of dependent input random variables, an innovative coupling between GPCE and score functions for calculating the second-moment sensitivities with respect to the design variables, and a standard gradient-based optimization algorithm, establishing direct GPCE, single-step GPCE, and multi-point single-step GPCE design processes. New analytical formulae are unveiled for design sensitivity analysis that is synchronously performed with statistical moment analysis. Numerical results confirm that the proposed methods yield not only accurate but also computationally efficient optimal solutions of several mathematical and simple RDO problems. Finally, the success of conducting stochastic shape optimization of a steering knuckle demonstrates the power of the multi-point single-step GPCE method in solving industrial-scale engineering problems.

An improved multiple quality characteristic analysis chart for simultaneous monitoring of process mean and variance of steering knuckle pin for green manufacturing

To solve the problems of overconsumption and the increasing environmental pollution brought by rapid industrial development, governments around the world have been introducing a series of green manufacturing (GM) policies to reduce the negative effects of manufacturing. A high-quality product means less time wasted on interruptions and restarts in the production process as well as less waste and defective products. However, once the quality of the product reaches a certain level (e.g., five Sigma), it becomes harder to attain greater economic and environmental benefits. Clearly, both excessive and inadequate quality exert a profound impact on corporations, society, and the environment. This study presents an improved Qpm multiple quality characteristic analysis chart (Qpm MQCAC) to ensure that product quality meets a specified standard with minimum input. Quality optimization is used to improve quality characteristics which do not meet the standard by joint monitoring of possible shifts in the process mean µ and/or process standard deviation σ. A guide is also provided to ensure successful quality improvement. The proposed approach not only identifies the factors that influence production quality, but avoids excessive consumption of resources, thereby achieving GM goals. The proposed approach is demonstrated in a step-by-step manner using the example of a steering knuckle pin. Future works are also discussed.

Optimization of fatigue life and fractography analysis of knuckle joint

Steering knuckle is an important component of a vehicle suspension system, which acts as a connection point between the wheel hub and the suspension system. Since, the forces coming from the tires are transferred to knuckle with high varying loads. The design of a knuckle becomes very critical in terms of its life with high factor of safety. At the same time, the design also should be robust with the required fatigue life, right material selection and weight optimization, without affecting the desired performance. There has been a considerable effort placed in this direction to reduce the overall weight of the knuckle system by employing high strength alloys instead of conventional materials or optimizing the geometry without altering the desired functionality and its fatigue life. This project focuses on optimization and fatigue life estimation of an optimized Knuckle using Finite Element Analysis approach and fatigue tester. This is done by studying and comparing the results of a rigid baseline model with that of an optimized model through simulation and experimentation. The optimized model is arrived based on the stresses obtained from the baseline study. The fatigue life of the optimized model is evaluated under fatigue tester and fractography analysis is carried out.