Automotive Crankshaft Research Articles

Tribological and Mechanical Behavior of Automotive Crankshaft Steel Superficially Modified Using the Boriding Hardening Process

One of the primary challenges in the automotive industry is the wear of engine components, such as the crankshaft and camshaft, which is the most pronounced during the engine’s startup phase, when the amount of lubricant fluid is at its lowest. This study aims to enhance the surface wear resistance of automotive crankshaft steel by applying a boriding thermochemical process. This process forms a hard surface layer on the steel, improving its mechanical properties and bolstering its wear resistance, especially under dry conditions. Boride layers were achieved using the powder-pack boriding process in a conventional furnace, with meticulous treatment times of 2, 4, and 6 h at a constant temperature of 950 °C. The nature of the layers was analyzed using X-ray diffraction, and their tribological behavior was evaluated using the pin-on-disk test. The growth of the layers was directly proportional to the treatment time and was estimated at 145 µm and 48 µm for the 6 and 2 h of treatment, respectively. The surface hardness increased from 320 HV for the non-treated steel to 2034 HV for the sample exposed to 950 °C for 6 h. The results indicate a significant reduction in the coefficient of friction from 0.43 for the non-treated steel to 0.12 for the samples exposed to 950 °C for 6 h, suggesting potential wear protection during the engine starting period.

Fatigue failure prediction through Factor of Safety and Stress concentration in a malfunctioned AISI 4140 Automotive Crankshaft

Abstract The performance and safety of any vehicle relies on proper design of crankshaft. Crankshaft failure occurs mainly due to the combination of imbalance and minor deflections when the materials is subjected to combined bending and twisting. Failure analysis is crucial to identify the causes and modes of failure, in order to improve the service life of automotive crankshafts and prevent accidents. This research analyses the root cause of failure by testing a failed crankshaft of a twin cylinder diesel engine used in mini commercial vehicle runs around 80000 km. The important research gap identified as that there is no fool-proof techniques and validation procedures are followed in the service stations during its life cycle period. This investigation of a failed crankshaft provides detailed composition of material, its micro structure and mechanical properties. Further, rotary analysis, experimental modal analysis and mechanical testing of materials are helpful in characterizing proper materials to be selected and analyzing the root cause of failure. The experimental setup helps to test a crankshaft and its specimen as per ASTM testing procedures and the results are correlated with numerical analysis using ANSYS software. The objective of this investigation is to provide insights through failure analysis to the designers and manufacturers, thereby improve the reliability and safety of automotive crankshafts, ensure safe operation of the vehicle, and eventually minimize financial losses.

The Effect of Multi-Walled Carbon Nanotubes Additives on the Tribological Properties of Austempered AISI 4340 Steel

Due to a combination of optimal properties such as great strength, high hardness, good process ability, and good mechanical properties, AISI 4340 steel is widely used in many critical industrial applications such as nuclear, military, defense, and aerospace. It is also widely used in hydraulic forged machine tools, forged automotive crankshaft systems, shafts and gears, because of their improved characteristics, and its good tribological properties. The purpose regarding this work is to check the tribological characteristics of austempered AISI 4340 steel while dry and lubricated with machinery oil of SAE 30 grade as base oil. As received, AISI 4340 steel samples have been austempered to four definitely austenitic phase temperatures (850℃, 900℃, 1000℃, and 1050℃) for 90 minutes before being immersed in a mixture of potassium nitrite and sodium nitrite at 400℃ for 45 minutes. Friction and wear tests were then performed on austempered samples. Multi-walled carbon nanotube particles were blended at weight concentrations of 0.055, 0.1, 0.15, 0.20, 0.25, 0.30, 0.35, 0.40, and 0.45 with typical machinery oil of 30 grade as base lubricant oil. A pin on the disc wear configuration was used in the experimental investigation. The use of Multi-Walled Carbon Nanotube (MWCNTs) additives in the base oil resulted in a decrease in both friction coefficients and wear rates values when compared to typical base oil lubricant. The results also showed a reduction in both friction coefficients and wear rates as the sample's austempering temperatures were raised. Sliding surfaces were also photo micro graphed, and when the volume concentrations of Multi-Walled Carbon Nanotube particles in the normal base oil lubricant were increased, smoother surfaces with less damage were shown.

Tensile properties and fracture toughness at service temperatures of an optimized pearlitic ductile iron alloy for automotive crankshafts

Cast iron and forged steel have competed against each other for many years for different industrial applications. Crankshafts are one of the products where this competition is still active, both for heavy duty and light machinery applications. For the specific case of automotive crankshafts, high strength pearlitic cast iron grades have found a strong position in passenger car market niches. The mechanical performance data available for these specific ductile cast iron grades mostly come from room temperature tensile and impact testing. Nevertheless, the failure mode of cast iron crankshafts involves fracture mechanics, and their usual range of working temperatures goes from −20°C for cold starts to 120°C for top maximum lubricating oil temperature. This work covers this range by studying a high strength pearlitic cast iron employed to manufacture crankshafts both in terms of tensile, impact and fracture mechanics testing at −20°C, 22°C and 120°C. A specific molding pattern was designed to produce the desired materials, namely crankshafts and Y2 and Y3 wedges, which were cast in an industrial crankshaft manufacturing line. The results indicate that there is a relevant difference between the low temperature and the high temperature mechanical response of the studied cast iron. This finding is interpreted in terms of safety, as the crankshafts should not fail in service after the engine has started running and the lubrication has reached its steady state working temperature.

Influence of Deep Rolling and Induction Hardening on Microstructure Evolution of Crankshaft Sections made from 38MnSiVS5 and 42CrMo4

Abstract In order to improve properties of complex automotive components, such as crankshafts, in an application-oriented way, several surface hardening treatments can be applied. Concerning the material performance the definition of adequate process parameters influences the resulting surface properties and, thus, the effectiveness of surface hardening treatments. To analyze most relevant process-microstructure-property relationships, the present paper reports results obtained by two different well-established surface hardening procedures, i. e. deep rolling as a mechanical treatment and induction hardening as a thermal treatment. For each hardening process widely used crankshaft steel grades, i. e. a medium carbon 38MnSiVS5 microalloyed steel and a quenched and tempered 42CrMo4 were selected and thoroughly characterized upon processing, using equal parameter settings. The results reveal that deep rolling in contrast to induction hardening proves to be a less sensitive surface layer treatment with regard to small differences in the initial microstructure, the chemical composition and the applied process parameters. Differences in microstructure evolution with respect to the applied surface hardening treatment are studied and discussed for the highly stressed fillet region of automotive crankshaft sections for all conditions. In this context, high-resolution SEM-based techniques such as EBSD and ECCI are proven to be very effective for fast qualitative evaluation of induced microstructural changes.

Hybrid coupled damper for the mitigation of torsional vibrations and rotational irregularities in an automotive crankshaft: Concept and design subtleties

This paper presents a new configuration to tackle a twofold problem affecting a crankshaft: the torsional vibrations and the oscillation of the speed at the back end of the shaft due to the torque ripples created by the cylinders. These two phenomena already have industrial solutions, but the requirement levels increase and impose constant improvements. Moreover, the common vibration dampers rely on energy dissipation as heat, which in a context of waste reduction could be avoided. This concept relies on the association of an optimal passive mechanical damper, an electric circuit and electromechanical converters, without any external power supply, in order to ensure a safe operation. From a more fundamental point of view, these elements link a time-periodic correction and a nonstationary cyclic excitation. The core idea of the concept is to enable a redistribution of the energy within this coupled electromechanical circuit, where each element can behave as a power consumer or supplier, so that the oscillations of the mechanical elements can be decreased. In this paper, the authors describe and model this new concept in order to investigate the resulting dynamic behavior and the key design parameters that affect the damping performance.

Study on Failure Analysis of Crankshaft Using Finite Element Analysis

Crankshaft is one of the crucial parts for the internal combustion engine which required effective and precise working. In this study, the aim of the study is to identify the stress state in the crankshaft and to explain the failure in automotive crankshaft and fatigue life of crankshaft by using finite element analysis. The 3D solid modelling of the crankshaft model was designed and developed using SolidWorks. A static structural and dynamic analysis on an L-twin cylinder crankshaft were used to determine the maximum equivalent stress and total deformation at critical locations of the crankshaft. The model was tested under dynamic loading conditions to determine fatigue life, safety factor, equivalent alternating stress and damage using the fatigue tool. The results obtained from this study indicated that the crankshaft has obvious fatigue crack which was belongs to fatigue fracture. The fatigue fracture developed was only attributed to the propagating and initiate cracks on the edges of the lubrication hole under cyclic bending and torsion. Overall, the crankshaft is safe for both static and fatigue loadings. In dynamic analysis, the critical frequency obtained in the frequency response curve should be avoided which it may cause failure of the crankshaft.

On assessing grindability of recycled and ore-based crankshaft steel: an approach combining data analysis with material science

Material-related grindability variations when grinding recycled and ore-based steel can significantly impair the process efficiency during finishing of automotive crankshafts. To address this problem and to achieve more robust grinding processes, the underlying causes of variation need to be understood. The present work investigates the feasibility of using quality data obtained during production to study grindability variations and identify material-related effects. Analysis of non-destructive inspection protocols indicates steel supplier-dependent differences in grindability. However, no systematic grindability differences between recycled and ore-based steel could be identified. Possible correlations between grindability and material characteristics obtained from supplied steel certificates are discussed.

A Comprehensive Review on AISI 4340 Hardened Steel: Emphasis on Industry Implemented Machining Settings, Implications, and Statistical Analysis

Turning of hardened AISI 4340 steel is regarded as one of the demanding challenges in machining sectors where precision tolerances are essential for automobile parts. The AISI 4340 steel is broadly utilized in forged steel automotive crankshafts systems, hydraulic forged and additional machine tool purposes because of their improved characteristics. Moreover, one of the keys confronts in the machining of hard 4340 steel is the comparatively deprived machining behavior that reduces the functionality of the material and further leads to component rejection at the final inspection stage. In addition, accelerated tool wear necessitates for repeated changing of cutting tool that results in higher machining and tooling costs. This comprehensive review aimed to present in-depth features on the development of machining performances using various cutting tools. This review focus is to provide a broad perceptive of the role of controllable variables during machining of hardened steel. This review analysis examines the response variables and its advantages on chip morphology and heat generation. The comprehensive overview of machining settings, key machinability indicators and statistical analysis for AISI 4340 steel has been presented. This overview will provide academic, industrial and scientific communities with benefits and shortcomings through improved conceptual understanding towards further research and development.

Fatigue reliability assessment in time domain using stochastic-induced random stress loads due to limited experimental data

This study aims to determine the fatigue reliability of an automotive crankshaft by stochastically inducing random loads because of limited experimental data. Given the difficulties in capturing actual load–time history data from laboratory or field-testing and the lack of loading history data, the corresponding stochastic modellings are formulated. The maximum and minimum loads obtained from the automobile industry at various rotational speeds are stochastically induced to generate random loads for assessing fatigue reliability. Fatigue life is evaluated using the Coffin–Manson, Morrow and Smith–Watson–Topper models in the time domain using the rainflow cycle counting technique. Weibull distribution is identified as the best fit of the data for fatigue lives on the basis of Akaike’s information criterion and is used to model reliability and hazard rate. Reliability below 0.09 with a hazard rate of over 1.35 × 10−5 is proposed as the high-risk regions according to the mean number of cycles to failure obtained from the fatigue life models. Thus, stochastic-induced random loads can assess the hazard rate-reliability from fatigue life data to predict the durability and structural integrity of components.

First Time Quality Diagnostics and Improvement through Data Analysis: A Study of a Crankshaft Line

Current enhancement of data availability and cloud technology provide a tremendous opportunity and platform for data-driven modeling and analyses in smart manufacturing. This paper proposes a data analysis framework to diagnose the root causes of first-time quality (FTQ), where FTQ is the quality of a part when it is measured the first time after all processes/operations in a production line. Due to the fact that too many inline factors in a production line with multiple operations may impact FTQ directly or indirectly, finding the key factors is essential yet difficult. An automotive crankshaft line is studied as an example. Production real-time inline data are collected and fetched from the data warehouse. After data preprocessing and exploratory analysis, a prediction model for FTQ is built through machine learning algorithms in Python. The data analysis identifies the significant process factors that influence the part quality, consequently improvement solutions and adjustment strategies could be generated based on the analysis. This study indicates the effectiveness and sustainability of data analysis and machine learning, as applied for quality diagnostics and improvement in manufacturing systems.

Numerical modelling of deep rolling influence over crankshaft bending and correlation with fatigue behaviour

AbstractThe requirements for mechanical reliability of automotive crankshafts are continuously increasing, thus pushing the demand for an optimized processing. Nonetheless, the manufacturing‐induced residual stresses at critical sites for fatigue enhancement are not clarified in the state‐of‐the‐art on the topic. In particular, there is a lack of information on the effect of final manufacturing stages to improve the component life endurance, such as deep rolling, in the overall stress state while the component is under operational loads. This study deepens the validation of a finite element deep rolling model under development with the aid of an in‐house developed crankshaft resonance fatigue test rig. The stress state obtained from the deep rolling simulation was input as a predefined stress field for the simulation of operational conditions experimented at the test rig. Test results produced cracks at the fillet radii of the cast iron crankshafts as anticipated. Overlapping the fractography with the simulation's final stress field yielded interesting correlation with the crack morphology. This contributed with a strong indication of the model correctness. Moreover, it can be further implemented to indicate whether the process parameters such as roller force and angle are fully optimized for each particular crankshaft application.

Determining the effect of ball burnishing parameters on surface roughness using the Taguchi method

Abstract Burnishing is a low-cost surface treatment process and can be used efficaciously to reduce the surface height and increase of the surface hardness of a workpiece. Low surface roughness and good fatigue behaviours of some engineering components are becoming now more important. Main applications are automotive crankshaft, inner and outer bearings races, bogies axles, etc. Ball burnishing process parameters such as burnishing speed, burnishing feed, burnishing force and burnishing width were considered to minimize the surface roughness. The ball burnishing experiment were planned as per L9 orthogonal array and signal to noise (S/N) ratio was applied to measure the proposed performance characteristics. The significance of the parameters on characteristics of the hydrostatic burnishing process have been evaluated quantitatively with the analysis of variance method.

Implementation of Reverse Engineering for Crankshaft Manufacturing Industry

In this modern world, there are always pressure on the designers and the manufacturers to respond to the consumer needs. Engineering involves designing, manufacturing, constructing, and maintaining of products, systems, service and structures. In this paper, an attempt has been made to derive all the parameters, which are necessary for designing the components of an engine using reverse engineering. Even though lots of methods are available for redesigning, the reverse engineering is selected. Computer aided modeling using CATIA and optimization analysis of crankshaft is used to study was to evaluate and compare the fatigue performance of three different materials of automotive crankshafts, namely forged steel, ductile cast iron and aluminium alloy. In this study a dynamic simulation was conducted on three crankshafts, cast iron and aluminum alloy forged steel; from similar single cylinder four stroke engines. The dynamic analysis was done and was verified by simulations in ANSYS. Geometry, material and manufacturing processes were optimized considering different constraints, manufacturing feasibility and cost.The maximum stress point and dangerous areas are found by the deformation analysis of crankshaft. Possible weight reduction options and their combinations were considered. Thus durability of feasible material and analysis is carried after weight reduction carried to the feasible material. Thus more possibilities of feasible crankshaft are found out.

Mechanical failure analysis of automobile crankshafts under service reconditioned modelling approach

Abstract Mechanical failure of automotive crankshaft is modelled under varying service reconditioning. Primary factors (torsional vibration, bending vibration and twisting) and secondary factors (lubricity of engine, oil quality, and lubrication effectiveness) responsible for failures were identified. The stated factors were modelled using service life of main journal bearings at varying operation speeds as the crankshaft failure predictors under different reconditioning. Modelling was carried out based on standard relationships among the stated factors. The system model was implemented using experimental data from the selected vehicular crankshafts. The results showed that the service life (failure) time of the crankshafts were dissimilar. Unequal useful life of the crankshafts was attributed to variation in torsional vibration and lubricity. The findings will serve as guides for selecting right vehicular crankshaft(s) based on targeted useful life and reconditioning limits.

Energy-Efficient optimization of forging process considering the manufacturing history

Increasing the energy efficiency of manufacturing processes is one of the many ways to reduce manufacturing cost and to resolve environmental issues. This paper systematically investigates the manufacturing process of an automotive crankshaft via a numerical simulation approach towards energy savings. The aim of this work is to propose potential solutions for improving the energy efficiency of the forging process chain in which energetically relevant parameters are optimized variables. The process chain is holistically optimized because the manufacturing history among the different processing steps is considered. We developed a discrete-event simulation based method to facilitate the holistic optimization of the forging process chain with regards to energy efficiency. To elucidate the weaknesses of the current process chain, manufacturing data were examined. Subsequently, a discrete-event simulation (DES) model was used in conjunction with design of experiments (DOE) in order to determine significant parameters as well as optimization scenarios. Finally, energy consumption optimizations were realized based on a consideration of the parameter adjustments. The research results show that the energy efficiency of the forging process chain could be improved by approximately 10% compared to the current state. Therefore, this work contributes to make the manufacturing crankshaft become greener and more efficient.

Multiobjective Optimization of the Heating Process for Forging Automotive Crankshaft

This paper presents potential approaches that increase the energy efficiency of an in-line induction heating system for forging of an automotive crankshaft. Both heat loss reduction and optimization of process parameters are proposed scientifically in order to minimize the energy consumption and the temperature deviation in the workpiece. We applied the numerical multiobjective optimization method in conjunction with the design of experiment (DOE), mathematical approximation with metamodel, nondominated sorting genetic algorithm (GA), and engineering data mining. The results show that using the insulating covers reduces heat by an amount equivalent to 9% of the energy stored in the heated workpiece, and approximately 5.8% of the energy can be saved by process parameter optimization.

Crankshaft failure analysis of a boxer diesel motor

This paper reports a failure mode analysis of a boxer diesel engine crankshaft. Crankshafts are components which experiment severe and complex dynamic loadings due to rotating bending combined with torsion on main journals and alternating bending on crankpins. High level stresses appear on critical areas like web fillets, as well as the effect of centrifugal forces and vibrations. Since the fatigue fracture near the crankpin-web fillet regions is one of the primary failure mechanisms of automotive crankshafts, designers and researchers have done the best for improving its fatigue strength. The present failure has occurred at approximately 2000 manufactured engines, and after about 95,000km in service. The aim of this work is to investigate the damage root cause and understand the mechanism which led to the catastrophic failure. Recommendations for improving the engine design are also presented.

Markov chain modelling of reliability analysis and prediction under mixed mode loading

The reliability assessment for an automobile crankshaft provides an important understanding in dealing with the design life of the component in order to eliminate or reduce the likelihood of failure and safety risks. The failures of the crankshafts are considered as a catastrophic failure that leads towards a severe failure of the engine block and its other connecting subcomponents. The reliability of an automotive crankshaft under mixed mode loading using the Markov Chain Model is studied. The Markov Chain is modelled by using a two-state condition to represent the bending and torsion loads that would occur on the crankshaft. The automotive crankshaft represents a good case study of a component under mixed mode loading due to the rotating bending and torsion stresses. An estimation of the Weibull shape parameter is used to obtain the probability density function, cumulative distribution function, hazard and reliability rate functions, the bathtub curve and the mean time to failure. The various properties of the shape parameter is used to model the failure characteristic through the bathtub curve is shown. Likewise, an understanding of the patterns posed by the hazard rate onto the component can be used to improve the design and increase the life cycle based on the reliability and dependability of the component. The proposed reliability assessment provides an accurate, efficient, fast and cost effective reliability analysis in contrast to costly and lengthy experimental techniques.

Stress Analysis on an Automotive Crankshaft under Mixed Mode Loading

The failures of the crankshafts are constantly subjected to cyclic loading which will tend to display the effects of fatigue that is stochastic in nature. The maximum bending moment occurs during the combustion cycle, where the direction of forces acting on the crankshaft will be exactly towards the centre of the crank radius. The torsional stress occurs during the power cycle can be considered as a quasi-static torsion as it is in steady condition. The aim of this paper is to illustrate the development of the analytical stress analysis used to determine mixed mode loading acting on the crankshaft. The analytical method developed according to the geometric ratio of the connecting rod and crankpin web to determine the variation of bending moment and torsional stress. It was observed that the maximum bending moment and torsional stress acting on the crankshaft are at angles and respectively due to the geometric ratio of the connecting rod and crankpin web. The analytical method that was derived and used for this study provides a good accuracy in determining the critical angles for bending moment and torsional stress acting on the crankshaft based on the geometric ratio.