Crash Box Design Research Articles

Design optimization for inner core of crash box for vehicle based on NPR/PU structure

Vehicle crashworthiness is a critical aspect of the passive safety domain in passenger cars, and crash boxes play a significant role in vehicle collisions. Currently, the crash boxes predominantly utilized in vehicles are primarily simple thin-walled structures, which exhibit average energy-absorbing capabilities. To enhance vehicle collision safety, this article proposes an inner core filled with negative Poisson’s ratio (NPR) structure and polyurethane (PU) material to the design of crash box. Initially, a double-arrow type NPR structure is selected as the framework, with polyurethane (PU) serving as the filling material. This combination forms the inner core of the crash box. A collision analysis is conducted on three types of crash boxes, examining the differences in their performance indicators in detail to demonstrate the superiority of the proposed design. Subsequently, variables that significantly influence the evaluation metrics were identified through extreme value difference analysis, and these variables were designated as the design parameters for the subsequent optimization process. Finally, the Neighborhood Cultivation Genetic Algorithm (NCGA) and Non-dominated Sorting Genetic Algorithm-II (NSGA-II) were employed as optimization algorithms for the optimal design, and the optimal results of the two algorithms are determined separately using Normal Boundary Intersection (NBI) method, and then compared to determine the overall optimal solution. The simulation results indicate that the NSGA-II optimized NPR/PU collision box provides substantial advantages in overall performance. After NSGA-II optimization, the NPR/PU crash box exhibits reduced overall collapse displacement and maximum peak collision force compared to other crash boxes, along with enhanced specific energy absorption capacity. These findings indicate that the designed NPR/PU crash box significantly improves the vehicle’s crashworthiness in the event of a collision. This article offers valuable theoretical insights to support the development and exploration of automotive crash boxes.

Multi‐parameter design optimization of crash box for crashworthiness analysis

AbstractThis study focuses on the optimization process of crash box design. The design optimization process is resource‐intensive and requires multiple dynamic simulations. Numerous design parameters can be varied to satisfy the crashworthiness objectives. Therefore an intelligent and robust machine learning (ML) framework has been developed. This framework can be employed to assist in the optimization of various crashworthiness components with different crashworthiness objectives.Here, a reinforcement learning‐based (RL) machine learning framework is developed. It consists of a finite element method (FEM) surrogate and RL environment. The FEM surrogate is trained using data from FEM simulations as well as synthetic data generated by a Generative Adversarial Network (GAN). An inverse problem is solved for optimizing the geometrical parameters of the boundary value problem while the RL is receiving input from the FEM surrogate. RL has proven to be accurate in many fields due to its ability to explore and exploit the learned dynamics. Conventional algorithms require numerous iterations and tuned functions to achieve appropriate results and need to be initialized after a slight change in the problem. Due to an optimization of input parameters in an inverse problem, RL is chosen for the present investigation.For the simulation data needed, the crash box is designed with linear first‐order accurate four nodal shell elements. Also, bilinear elastoplastic material along with geometrical nonlinearity is used to simulate the dynamic deformation process.The RL agents learn to vary the crash box design parameters and search for the optimal parameters. The optimal parameters are based on the user‐defined crashworthiness objectives.

Optimizing crash box design to meet injury criteria: a protocol for accurate simulation and material selection

The design of a deformation element or crash box that meets a given injury criterion based on deceleration requires careful consideration of physical properties and space requirements. Variations in material yield stress or geometry can result in statistical variations in the injury criterion output. Optimizing the crash box to fulfil two different injury criteria and two different energy levels may require more space than initially specified. In this study, we propose a protocol where the crash box is collapsed, and force–displacement is fitted to an equation. This fit is carried out with just two simulations and compared to 30 possible scenarios, obtaining a maximum error of 38.9%. With this initial fit, the appropriate thickness and yield stress can be chosen to perform crashes with two energy levels and monitor four injury values. With the ideal yield stress and sheet metal thickness, we introduce real statistical distributions using Monte Carlo design to perform 200 simulations and obtain 400 injury values for each design proposal. This technique ensures that the design will meet injury requirements for any possible combination of thickness and yield stress accepted by quality inspection. If only one simulation is performed, all designs meet the requirements, but only the last proposed design decreased the average injury to 9.2 g with a standard deviation of 2.68 g and a maximum value of 14.4 g, which is less than the required 15 g. This technique minimizes the risk of finding combinations of yield stress and thickness that produce an undesirable injury criterion.

Design of a Lightweight Origami Composite Crash Box: Experimental and Numerical Study on the Absorbed Energy in Frontal Impacts

Design of a Lightweight Origami Composite Crash Box: Experimental and Numerical Study on the Absorbed Energy in Frontal Impacts

Honeycomb structure design of automotive crash box

The crash box can protect the safety of passengers when a car collides. Due to its excellent mechanical properties, honeycomb structure can be applied to automotive crash boxes. Two kinds of crash boxes made of regular hexagonal honeycomb structure and re-entrant hexagonal honeycomb are designed. The research results indicate that, compared to the crash box made of hexagonal honeycombs, the crash boxes made of re-entrant hexagonal honeycombs have superior energy absorption ability. Furthermore, the influence of different structural parameters on the energy absorption performance (EAP) of the crash box made of re-entrant hexagonal honeycombs is analyzed. It is found that the total energy absorption and peak force increase with the increase of thickness and concave angle. The research in this article provides certain reference significance for the design of honeycomb structure crash boxes.

Accessing quasi-static impact process by 3D-NPR corrugated metamaterials

The conventional impact process is a quintessential impulse process that causes substantial damage due to the high initial impact force. However, the impact effect can be significantly diminished by making the impulse process quasi-statically by using a three-dimensional negative Poisson's ratio corrugated metamaterial (3D-NPRCM) structure. This paper proposes a novel 3D-NPRCM obtained by folding the 2D-NPRCM. This study examines the crashworthiness properties and impact force of 3D-NPRCM subjected to impact using the finite element method (FEM). The results reveal that the sequential matrix structure has the ability to make impact impulse processes quasi-statically. The effects of various folding angles, arrangements, and geometrical parameters on the properties are also explored. Finally, the 3D-NPRCM is employed in an automobile crash box design. Through axial quasi-static compression simulation, the peak crushing force of the 3D-NPRCM crash box is reduced by 25.374 % from 211.652 kN to 157.946 kN, and the energy absorbed is increased by 23.830 % from 11.259 kJ to 13.942 kJ, compared to the conventional crash box. Through cart lateral impact simulation, the peak crushing force of the 3D-NPRCM crash box is reduced by 18.076 % from 206.9 kN to 169.5 kN, and the compressive displacement is decreased by 9.457 % from 235.8 mm to 213.5 mm. This work presents a novel design proposition for a crash box in vehicle engineering and demonstrates a fresh approach to expand the design of three-dimensional mechanical metamaterials.

Crashworthiness Performance of Circular Hybrid Crash Box Due to Axial Load

In the previous study, hybrid crash box combines low-density and high strength of composite materials with aluminum materials had been developed. In this study, circular hybrid crash box with friction model is investigated. Crash box design is modelled by using computer simulation with ANSYS workbench. Composite carbon toray T300 – epoxy resin (CCE) and metal aluminum alloy 6063 (AA6063) is used as hybrid crash box material. Axial loading with a speed of 10 m/s is applied to circular hybrid crash box model by using impactor with mass of 100 kg. The orientation angle of composite lay-up and hybrid material configuration with two models of friction was running as 16 models. Energy absorption and deformation pattern were observed to determine crashworthiness performance. Based on the results, it can be denoted that the Al-Ko45 with friction model of 0.68 shows largest energy absorption of 7.53 kJ with specific energy absorption of 32.552 kJ/kg. The deformation pattern produces mixed mode with progressive crushing folding that can enhance energy absorption.

ENERGY ABSORPTION AND DEFORMATION PATTERN OF CIRCULAR HYBRID CRASH BOX SUBJECTED TO FRONTAL LOAD

Crashworthiness is related to the ability of a structure to reduce the effects of a collision risk of injury to passengers and the risk of damage to vital parts of the vehicle. Geometry design of crash box is one important parameter to increase crashworthiness performance by increasing energy absorption through progressive deformation. In previous studies, circular crash box absorbed higher energy than other geometry design. Besides that, another parameter is material design. In other studies, the hybrid model absorbs more energy with a less increasing mass. Hybrid crash box combine low-density and high-strength of composite materials with aluminium materials are affordable and ductile to increase energy absorption. This study aims to develop circular hybrid crash box by variating fibre orientation angle of composite and hybrid material configuration. Crash box design is investigated by using computer simulation with ANSYS Workbench. The crash box materials used are Carbon Toray T300 – Epoxy Resin (CCE) and Aluminium Alloy 6063 (AA6063). Eight of circular hybrid crash box models subjected to axial loading with a speed of 10 m/s. The frontal loading is modelled by setting impactor with mass of 100 kg. Energy absorption and deformation pattern were observed. The results showed that the Al-Ko45 model with orientation angle [45/- 45,-45/45]5 and hybrid material configuration of composite inside has highest energy absorption of 8.24 kJ. The deformation pattern in the aluminium part is mixed of concertina at the first stage then continued by diamond pattern, The deformation composite part is dominated by local buckling with transverse shearing. The fractions or folds of composite is functions like foam-filled filling folds of aluminium deformation to initiate progressive crushing folding that can increase the crashworthiness characteristic as the energy absorption.

Evaluation of Automotive Bio-Composites Crash Box Performance

In the automotive industry, sustainable materials, such as bio-composites, are progressively being adopted due to their lightweight feature, which reduces vehicle weight, fuel consumption and pollutants emissions. Bio-composites are renewable and biodegradable, making them more environmental-friendly. However, limited investigations into the use of bio-composites in crash box applications have indicated that they lack the impact strength to fully absorb collision energy. This study aims to compare the crashworthiness performance of crash boxes made from OPEFB fiber/epoxy and kenaf fiber/epoxy composites, with conventional steel and carbon fiber/epoxy using LS-DYNA quasi-static simulations. Six different crash box designs are proposed: square, hexagonal, decagonal, hexagonal 3-cell, hexagonal 6-cell, and decagonal 10-cell structure, to evaluate the effect of these designs on crash box performance. The results show that bio-composite crash boxes are inferior to traditional materials in terms of energy absorption and specific energy absorption, but they yield better performance in crush force efficiency. In terms of design, decagonal 10-cell structure produces the highest specific energy absorption and energy absorption for bio-composites. Hence, optimization is performed on the OPEFB fibre/epoxy decagonal 10-cell crash box, aiming to increase energy absorption capability by varying the thickness, perimeter, and length of the crash box. The design is optimized by increasing thickness and maintaining length and perimeter. Compared to the original design, the optimized design improves energy absorption by 59% and specific energy absorption by 19%. The optimized design is then subjected to both quasi-static and impact loading tests, revealing that the optimized OPEFB fibre/epoxy crash box design exhibits 44% lower energy absorption than steel under quasi-static load, but it demonstrates a 56% increase in crush force efficiency and a 6 % increase in specific energy absorption. Under impact load, it shows a 91% increase in specific energy absorption compared to the traditional square steel crash box.

Optimizing functionally graded hexagonal crash boxes with honeycomb filler for enhanced crashworthiness

A crash box is typically designed to enhance crashworthiness by absorbing impact energy and reducing the crushing force that can cause injury or fatality to passengers. However, the structural integrity of conventional crash boxes is often compromised due to buckling deformations during collisions. This study introduces a novel approach utilizing functionally graded thickness (FGT) in hexagonal crash box design with honeycomb fillers to improve crashworthiness through multi-objective optimization. Finite element analysis using LS-DYNA was performed for axial and oblique impacts. Mesh sensitivity study indicated that constructing the FGT crash box with 41 layers yielded favourable outcomes, with simulation results differing by a mere 2.5% compared to experimental data. A surrogate model based on response surface methodology was employed to mathematically formulate the objective functions, which aimed to maximize specific energy absorption (SEA) and minimize initial peak crash force (IPF). Subsequently, a multi-objective particle swarm optimization was used to determine the optimal grading exponent of both outer and filler structures. The optimized FGT crash box demonstrated superior control over progressive deformation, exhibiting high SEA and reducing IPF compared to the uniform thickness crash box. Particularly, under oblique impact loads, using two grading exponents in optimizing the FGT crash box potentially achieved significant improvements in crashworthiness within the design procedure.

Machine learning enhanced optimisation of crash box design for crashworthiness analysis

AbstractThe primary goal of the current study is to optimise crash box designs for automobiles. Machine learning (ML) techniques are used to build an intelligent and reliable ML framework. With the help of this framework, the crash box design can be optimised for crashworthiness analysis. The optimisation of the crash box design is resource‐intensive due to its intricate geometric design, use of a variety of materials, and extensive use of dynamic simulations to determine the ideal structural parameters through simulations. A reinforcement learning‐based (RL) optimization technique is developed for this reason. The crash box is built with nonlinear first‐order shear deformation shell elements to provide the necessary simulation data, and nonlinear elastoplastic material is used to model the dynamic impact process. The RL agents are tuned using finite element (FE) simulations and synthetic data generated by a generative adversarial network (GAN) to optimise and select the optimal model parameters for vehicle crashworthiness analysis. To estimate the correct model parameter required to fulfil specified crashworthiness metrics, the RL agent learns and optimises automatically. This method is effective in terms of resources and could be helpful in the early stages of vehicle development.

Crashworthiness Analysis of Vehicle Crash-Box Filled with Aluminium Foam

Lightweight, robust, and anti-rust properties of aluminium foam might be a solution for reducing the effect of traffic accidents and for minimum fuel consumption. This research investigated the crashworthiness of vehicle crash-box filled with aluminum foam by varying its cross-sectional structure and its loading angle such as 0°, 10°, 20°, 30°. The variations consisted of structures for example single wall foam filled and double wall foam filled. The material used to construct the wall was Aluminum Alloy 2024 and Aluminium foam. The finite element model using Abaqus CAE Software was operated for both designing the crash-box and analyzing its crashworthiness. Some parameters were determined To obtain the best crash-box design, the finite element analysis was carried on total energy absorption, specific energy absorption, maximum load, average load, and crush-force efficiency. Double wall foam filled crash-box was shown to have better energy absorption ability and this structure of crush box is considered fpr vehicle structure in future.

MULTI-OBJECTIVE DESIGN OF HONEYCOMB HYBRID CRASH BOX UNDER FRONTAL LOADING

This research aims to obtain the optimal honeycomb hybrid crash box design. Finite elements, parametric studies, and multi-objective optimization are carried out sequentially. Parametric studies are carried out to obtain important parameters to increase energy absorption and minimize mass. The effect of structure angle, honeycomb side length, and structure thickness are selected as the design parameter. Energy absorption and crash box mass are observed as design responses. Based on the results, it can be determined the optimal design from multi objective optimization is angle structure of 21.1310, side length of 8.006 mm, and thickness of 1.2 mm. The model validation results for the optimal solution are appropriate; it is characterized by a honeycomb-filled structure that supports the folding of the outer wall of the crash box.

Development of Bi-hexagonal hybrid crash box subjected to axial loading for enhancement of crashworthiness

Crash box design had been developed to increase crashwortiness performance. The crash box cross section is one important parameter to increase the energy absorption as crashwortiness performance. In the previous study, hexagonal cross section provide the higher energy absorption than other cross section. One of strategy to increase cross section is using two cross section put together in one component of crash box design. Bi-tubular crash box shows higher energy absorption with easy manufacture opportunity. In other study, hybrid crash box is investigated to reduce crash box mass. In this study, development of bi-hexagonal hybrid crash box subjected to axial loading to enhance crashworthiness were investigated. Analysis of crash box design is developed by using computer simulation with ANSYS Workbench 19.2. The crash box materials used are Aluminum Alloy and carbon-epoxy woven. The material modeling in the crash box is assumed as deformable body while the impactor is a rigid body. The axial loading is modelled by setting impactor impact the crash box with a speed of 7.67 m/s. Fixed support is set on the bottom of crash box. Nine of frontal test models were simulated for the bi-hexagonal hybrid crash box with different layups orientation angle and composite hexagonal tube diameter. Energy absorption and deformation patterns were observed. The results indicated that the highest energy absorption and specific energy absorption is occured on the A60 model with layups orientation angle of [0/60/0/60] and composite hexagonal tube diameter of 41 mm are 3693.8 J and 19.121 kJ/kg. The deformation pattern in the aluminum part is diamond mode, while in the composite part, the deformation pattern produce transverse shearing, lamina bending, brittle fracturing and local buckling mode

COMPUTER SIMULATION INVESTIGATION OF CRASH BOX DESIGN AS SAFETY-PROTECTION TECHNOLOGY FOR INDONESIA HIGH SPEED TRAIN

The crashworthiness of a railway vehicle has been developed to provide energy absorption capacity and efficiency of energy absorption. This study presents a computer simulation to determine the energy-absorbing structure of the new addition of a crash box design on the Indonesian high-speed train in a collision scenario. The crashworthiness analysis in the crash box is done with software based on finite element methods. The crash box is modeled as a thin-walled structure located in coupler housing, between the draft gear and the car frame. The test model was carried out according to the 2019 SNI 8826 standard using a frontal impact test with an impactor mass of 38.807 kg and a speed of 10 m/s. The pattern of deformation and energy absorption is obtained by calculating the area under the graphical curve of the relationship between the force reaction and the displacement obtained from the simulation. The deceleration of the train is obtained from the graph of acceleration against time on the impactor. The simulation results show that the addition of a crash box design as an energy absorption module on a safety protection technology for railway vehicles can reduce the severity of the impact and improve passenger safety. The application of the initial crash box model also shows an unacceptable train deceleration in the SNI 8826 test standard.

Combination of frustra shapes with cross sections and trigger circles for crash box design to absorb energy

Crash box that has not been maximal in absorbing energy during collisions are the basis for researchers to redesign crash box. There are three designs of crash box that combined frustra, cross section with three holes. This is a novel design that is expected to absorb more energy and minimize deformation and also buckling. The finite element simulation shows that the square model can absorb higher energy than the other two models, that is 142.66 KJ at 0.005 s, a force of 5728 KN, and displacement of 57 mm. Therefore, the recommended shape from this research is the square model.

3G-optimization of multi-cell crash box cross-section of autobody based on crashworthiness

The cross-section, thickness, and material of the autobody structure determine the crashworthiness and lightweight level. Different from the variables in traditional autobody design that are considered separately, the basic theory of 3G-optimization is to simultaneously consider geometric shape (Geometry), the thickness of structure (Gauge), and material grade (Grade) in structural optimization design, which is conducive to maximizing the lightweight potential of the structure. This paper presents a cross-section optimization method for multi-cell thin-walled structures based on 3G-optimization, which is used in the structural design of crash box. Based on full width frontal collision condition, the cross-section shape, thickness, and material variables of the multi-cell crash box are optimized simultaneously. Multiple sets of optimization schemes show obvious weight reduction effect while ensuring safety. Besides, the sub-system decoupling method and hybrid cellular automaton (HCA) method are applied to 3G-optimization process, which is beneficial to improve the calculation efficiency and provide a theoretical basis for the definition of the initial design space for 3G-optimization.

Effect of heat-treatment on crash performance in bumper beam and crash box design and optimization of the system

Abstract Within the study’s scope, impact analyses of homogeneous bumper beam-crash box systems designed from AA6063-O, AA6063-T5, and AA6063-T6 materials and hybrid systems designed from combinations of these materials were made and compared in terms of energy absorption values. In designs where failure does not occur, the highest energy absorption value was obtained using the AA6063-T5 bumper beam and AA6063-O crash box system, and single and multi-objective optimization studies were conducted using this design. The optimal bumper system improved the crash performance of the structure. Accordingly, this bumper system can be used in vehicles to improve crashworthiness.

An investigation of the crashworthiness performance and optimization of tetra-chiral and reentrant crash boxes

In this study, the crash performances of square and cylindrical crash boxes with tetra-chiral and reentrant unit cell structures were explored and optimized. First, tensile tests were conducted to determine the mechanical properties of the Al 6061-T6. These mechanical properties were then incorporated in the finite element (FE) models generated using LS-DYNA. To validate the FE models, tetra-chiral and reentrant crash plates were produced, and the FE analysis results were compared with the test results. Subsequent to this validation, for each crash box design type (i.e., tetra-chiral cylindrical, tetra-chiral square, reentrant cylindrical, and reentrant square), Kriging surrogate models were constructed using MATLAB for two crash metrics: specific energy absorption (SEA) and crash load efficiency (CLE). Finally, a multi-objective optimization problem was formulated for each crash box design type, the generated Kriging models are integrated into genetic algorithm available in MATLAB, and the Pareto optimal crash box designs were obtained. It was found that the SEA and CLE of reentrant crash boxes were better than those of the tetra-chiral crash boxes. In addition, the reentrant cylindrical crash box displayed better performance than the reentrant square, as well as the tetra-chiral cylindrical and square crash boxes.

Exploration-oriented sampling strategies for global surrogate modeling: A comparison between one-stage and adaptive methods

Studying complex phenomena in detail by performing real experiments is often an unfeasible task. Virtual experiments using simulations are usually used to support the development process. However, numerical simulations are limited by their computational cost. Metamodeling techniques are commonly used to mimic the behavior of unknown solver functions, especially for expensive black box optimizations. If a good correlation between the surrogate model and the black box function is obtained, expensive numerical simulations can be significantly reduced. The sampling strategy, which selects a subset of samples that can adequately predict the behavior of expensive black box functions, plays an important role in the fidelity of the surrogate model. Achieving the desired metamodel accuracy with as few solver calls as possible is the main goal of global surrogate modeling. In this paper, exploration-oriented adaptive sampling strategies are compared with commonly used one-stage sampling approaches, such as Latin Hypercube Design (LHD). The difference in the quality of approximation is tested on benchmark functions from 2 up to 30 variables. Two novel sampling algorithms to get fine-grained quasi-LHDs will be proposed and an improvement to a well-known, pre-existing sequential input algorithm will be discussed. Finally, these methods are applied to a crash box design to investigate the performance when approximating highly non-linear crashworthiness problems. It is found that adaptive sampling approaches outperform one-stage methods both in terms of mathematical properties and in terms of metamodel accuracy in the majority of the tests. A proper stopping algorithm should also be employed with adaptive methods to avoid oversampling.