Vehicle Front Structure Research Articles

A Hierarchical Prediction Method for Pedestrian Head Injury in Intelligent Vehicle with Combined Active and Passive Safety System.

With the development of intelligent vehicle technology, the probability of road traffic accidents occurring has been effectively reduced to a certain extent. However, there is still insufficient research on head injuries in human vehicle collisions, making it impossible to effectively predict pedestrian head injuries in accidents. To study the efficacy of a combined active and passive safety system on pedestrian head protection through the combined effect of the exterior airbag and the braking control systems of an intelligent vehicle, a "vehicle-pedestrian" interaction system is constructed in this study and is verified by real collision cases. On this basis, a combined active and passive system database is developed to analyze the cross-influence of the engine hood airbag and the vehicle braking curve parameters on pedestrian HIC (head injury criterion). Meanwhile, a hierarchy design strategy for a combined active and passive system is proposed, and a rapid prediction of HIC is achieved via the establishment of a fitting equation for each grading. The results show that the exterior airbag can effectively protect the pedestrian's head, prevent the collision between the pedestrian's head and the vehicle front structure, and reduce the HIC. The braking parameter H2 is significantly correlated with head injury, and when H2 is less than 1.8, the HIC value is less than 1000 in nearly 90% of cases. The hierarchy design strategy and HIC prediction method of the combined active and passive system proposed in this paper can provide a theoretical basis for rapid selection and parameter design.

A parametric metamodel of the vehicle frontal structure accounting for material properties and strain-rate effect: application to full frontal rigid barrier crash test

In the automotive industry, building parametric surrogate models is a fundamental tool to evaluate, in real time, the performance of newly designed car components. Such models allow to compute any Quantity of Interest —QoI—, such as a specific safety protocol index, for any choice of material and/or geometrical parameters characterizing the component, within the stringent real time constraint. For instance, they can be exploited to guarantee safer designs (e.g., maximizing energy absorption by the crash boxes) or to reduce manufacturing costs (e.g., minimizing the mass of a specific structure under some safety protocol constraints). In general, these parametric simulation tools allow a significant gain in terms of manufacturing costs and time delays during the investigation phase. In this study, we focus on the vehicle frontal structure system considering its performance in a full-frontal crash scenario. In the front structure system we parameterize the crash boxes (left and right) and the inner/outer side front members (left and right, front and rear) with respect to the part thickness and the material parameters characterizing the Krupkowski plasticity curve. Moreover, Strain Rate Effect is also taken into account via Neural Network based regressions, whose training dataset comes from experimental data. The parametric metamodel is built via Non-Intrusive PGD —NI–PGD— strategies, relying on a sparse sampling of the parametric space, and allowing a quite reduced number of High Fidelity —HiFi— simulations. A novel strategy based on clustering and classification, known as Multi-PGD, is also applied and numerically verified.

Multiobjective discrete optimization using the TOPSIS and entropy method for protection of pedestrian lower extremity

Design of vehicle frontal structures signifies an important topic of studies on protection of pedestrian lower extremity. Conventional optimization has been largely focused on continuous variable problems without involving complexity of human model. Nevertheless, design of frontal structures is commonly discrete from a manufacturing perspective and the responses of the lower extremity of pedestrian are highly nonlinear in nature. For this reason, this study aimed to develop a multiobjective discrete optimization (MODO) algorithm for design of frontal structures involving a pedestrian model. In the proposed MODO method, the order preference by similarity to ideal solution (TOPSIS) was coupled with the entropy algorithm to develop a multiple attribute decision making (MADM) model for converting multiple conflicting objectives into a unified single cost function. The presented optimization procedure is iterated using the successive orthogonal experiment to deal with a large number of design variables and design levels. In this study, the proposed method was first verified by two benchmark examples; and then was applied to a more sophisticated real-life design case of vehicle frontal structure to better protect pedestrian lower extremity from impacting injury. The finite element model was validated via experimental tests first and the optimized design was then prototyped for the further physical tests. The results showed that the algorithm is able to achieve an optimal design in a fairly efficient manner. The proposed algorithm exhibits considerable potential to solve other complex engineering design problems.

Metamodel-Based Multi-Objective Reliable Optimization for Front Structure of Electric Vehicle

In this paper, a multi-objective reliable optimization (MORO) procedure for the front body of an electric vehicle is proposed and compared with determinate multi-objective optimization (DMOO). The energy absorption and peak crash force of the simplified vehicle model under the full-lap frontal impact condition are used as the design objectives, with the weighted sum of the basic frequency, the first-order torsional and bending frequencies of the full-size vehicle model, and the weight of the front body taken as the constraints. The thicknesses of nine components on the front body are defined as design variables, and their geometric tolerances determine the uncertainty factor. The most accurate metamodel using the polynomial response surface, kriging, and a radial basis function is selected to model four design criteria during optimization, allowing the efficiency improvement to be computed. Monte Carlo simulations are adopted to handle the probability constraints, and multi-objective particle swarm optimization is employed as the solver. The MORO results indicate reliability levels of $$R = 100$$ %, demonstrating the significant enhancement in reliability of the front body over that given by DMOO, and reliable design schemes and proposals are provided for further study.

Analysis of pedestrian-to-ground impact injury risk in vehicle-to-pedestrian collisions based on rotation angles

IntroductionDue to the diversity of pedestrian-to-ground impact (secondary impact) mechanisms, secondary impacts always result in more unpredictable injuries as compared to the vehicle-to-pedestrian collisions (primary impact). The purpose of this study is to investigate the effects of vehicle frontal structure, vehicle impact velocity, and pedestrian size and gait on pedestrian-to-ground impact injury risk. MethodA total of 600 simulations were performed using the MADYMO multi-body system and four different sizes of pedestrians and six types initial gait were considered and impacted by five vehicle types at five impact velocities, respectively. The pedestrian rotation angle ranges (PRARs) (a, b, c, d) were defined to identify and classify the pedestrian rotation angles during the ground impact. ResultsThe PRARs a, b, and c were the ranges primarily observed during the pedestrian landing. The PRAR has a significant influence on pedestrian-to-ground impact injuries. However, there was no correlation between the vehicle velocity and head injury criterion (HIC) caused by the secondary impact. In low velocity collisions (20, 30km/h), the severity of pedestrian head injury risk caused by the secondary impact was higher than that resulting from the primary impact. ConclusionsThe PRARs defined in this study are highly correlated with the pedestrian-to-ground impact mechanism, and can be used to further analyze the pedestrian secondary impact and to predict the head injury risk. Practical applicationsTo reduce the pedestrian secondary impact injury risk, passive and active safety countermeasures should be considered together to prevent the pedestrian's head-to-ground impacts, particularly in the low-velocity collisions.

Methodological approach for reducing computational costs of vehicle frontal crashworthiness analysis by using simplified structural modelling

ABSTRACTA challenge in the design and optimisation of the vehicle front structures is the high computational costs required for crash analysis. A methodological approach to simplifying finite element vehicle models and crash barriers is presented in this paper. The methodology uses global deformation characteristics of structures which are obtained from the global crash model. For the simplification of the vehicle crash model, structural regions which sustain only elastic deformations during the frontal crash are replaced by kinematic numerical representations which describe both stiffness and load paths at the interface of the substituted structures. Verification studies of the simplified vehicle model show a very good agreement of the global and local structural response during the frontal crash. Further simplifications were applied to the offset deformable barrier by replacing its detailed crushing behaviour by kinematic descriptions. Through the combined use of both simplified numerical representations, the computational cost of a Euro new car assessment program (NCAP) offset crash analysis can be reduced by around 92%. With the obtained time reduction, structural optimisation studies of the remaining structure can be conducted efficiently for the identification of weight reduction potentials.

Numerical study for identification of influence of energy absorption and frontal crush for vehicle crashworthiness

According to the statistics it has been seen that everyday nearly 400 people are killed due to road accidents. Due to this it has become an important concern to concentrate on the safety of the passengers which can be done by improving the crashworthiness of the vehicle. During the impact, a large amount of energy is released which if not absorbed, will be transmitted to the passenger compartment. For the safety of the passenger this energy has to be absorbed. Front rail is one of the main energy absorbing components in the vehicle front structure. When it comes to the structure and material of the part or component of the vehicle that is to be designed for crash, it is done based on three parameters: Specific Energy of Absorption, Mass of the front rail and maximum crush force. In this work, we are considering different internal geometries with different materials to increase the energy absorbing capacity of the front rail. Based on the extensive analysis carried aluminium seizes to be the opt material for frontal crash.

Strength Enhancement of Car Front Bumper for Slow Speed Impact by FEA Method as per IIHS Regulation

Low speed collisions happen significantly due to on road slow moving heavy traffic as well as during parking of vehicles. The bumpers are provided in front and back side of a vehicle has two main purposes: first is to absorb the energy generated during these kinds of slow speed impacts and secondly to protect the expensive parts like main engine parts, radiators and connected engine cooling mechanism, headlights, taillights, etc, by slowing down the vehicles. The problem often in various cars bumper is that they doesn’t line-up vertically during low speed impact and leads to damage of various parts which are costly to repair. Many a times bumper design does not have sufficient capacity to absorb the energy generated during these impact. Guideline by International Institute Highway Safety (IIHS) regulation provides useful insight for such low speed impact study. In this paper, slow speed impact test were conducted as per IIHS regulation in three positions namely central impact, left hand corner impact and right hand corner impact. Parameters including bumper material, shape, thickness and impact condition are analyzed using fine element analysis (FEA) to enhance crashworthiness design in low speed impact. Then the vehicle front structure has been modified suitably. It has been observed that lining up the front metal bumper with suitable stiffness provides the best result which ultimately reduces the damage to the vehicle parts.

Multiobjective reliability-based design optimisation for front structure of an electric vehicle using hybrid metamodel accuracy improvement strategy-based probabilistic sufficiency factor method

ABSTRACTThe determinate multiobjective optimisation (DMOO) without considering effects of uncertainties on vehicle body design may fail to satisfy the desired property in practice. In this paper, a multiobjective reliability-based design optimisation (MORBDO) procedure is proposed to perform the design for front structure of an electric vehicle. In which, body performances including full-lap frontal crashworthiness, modal characteristic and lightweight level are involved and coordinated, and the thickness of five key components with geometric tolerances are selected as design variables. Probabilistic constraint in MORBDO is addressed by Monte Carlo simulation (MCS) technique-based probabilistic sufficiency factor (PSF) method. To improve the accuracy of optimisation results, a closed-loop system named hybrid metamodel accuracy improvement strategy is presented here by organising adaptive optimum metamodel selection and the max–min distance approach-based new samples addition technique together. The optimisation problem is solved by the multiobjective particle-swarm-optimisation algorithm. The effectiveness of the proposed procedure is certified by successfully obtaining more accurate and reliable alternative optimum schemes in the design for the front body structure in comparison with DMOO, normal PSF method and safety factor method.

Lightweight Sandwich Structures in Innovative Vehicle Design under Crash Load Cases

On modern vehicles, the demand is made to be in every respect as efficient as possible. A technical method to increase energetic efficiency is to reduce the vehicle mass through the implementation of lightweight construction measures. The energy consumption decreases by that and the vehicle dynamics behavior of conventionally and alternatively respectively electrically powered vehicles increases. In the department Lightweight and Hybrid Design Methods of the Institute of Vehicle Concepts in Stuttgart in collaboration with 3A Composite Core Materials, a method which allows to realize sandwich structures for automotive structural applications analytically and conceptually, is developed. The development method based on material and component testing and material values would be determined at different loads, for example in pressure and in-plane tests. These values are transmitted into the analytical determination of so called failure mode maps to derive appropriate sandwich structures. With novel sandwich structures the objectives of high structural stiffness and strength are tracked, as well as a high level of energy absorption potential. By function integrating the potential of lightweight construction, depending on the energy absorption per structural weight, can be further increased. Accompanying tests on generic structures are made to validate the failure behavior. Also the influence of core material on the deformation behavior is examined. The results from the tests are transferred to a vehicle front structure of a planned lightweight vehicle of class L7E called "Safe Light Regional Vehicle" (SLRV). The behavior of the structure is examined in static and dynamic tests. The energy absorbing capacity can be further increased by geometric optimization and the use of different core materials. The research on sandwich materials is part of the research project Next Generation Car (NGC) of the DLR and represents in terms of the new vehicle concept SLRV in sandwich design a novel vehicle concept of this joint project.

The influence of gait stance on pedestrian lower limb injury risk

The effect of pedestrian gait on lower limb kinematics and injuries has not been analyzed. The purpose of this paper was therefore to investigate the effect of pedestrian gait on kinematics and injury risk to the lower limbs using the Total Human Model for Safety adult male pedestrian model together with FE models of vehicle front structures. The modeling results indicate that the tibia and femur cortical bone von-Mises stress and the lateral knee bending angle of an adult pedestrian are strongly dependent on the gait stance when struck by both a sedan car and an SUV at 40km/h. The gait analysis shows that generally the leg of an adult pedestrian has lower injury risk when the knee is flexed and linear regressions show high negative correlation between knee flexion angle during impact and knee lateral bending angle and also high negative correlation between lower leg axial rotation during impact and knee lateral bending angle. Furthermore, in some gait stances a self-contact between the legs occurs, and the peak bones stresses and knee shearing displacement in the leg are then increased. Assessment of pedestrian lower limb injury should take account of these gait stance effects.

Performance evaluation of vehicle front structure in crash energy management using lumped mass spring system

The design for vehicle structural crashworthiness which ensures that components of desired crash performance characteristics are used in product manufacturing essentially involves the evaluation of the energy absorption potentials of the structures using suitable computation method. Due to unresolved difficulties in achieving detailed results through the existing methods researchers seek for more alternative computation methods. Although previous efforts in this regard are quite significant, yet some concerns still exist on accuracy or computational efficiency achievable through the conventional methods. The lumped mass spring (LMS) method is applied in the present study. Some new steps were introduced in the basic procedure to improve the accuracy and computational efficiency of the method. A new dynamic stiffness formula is written in terms of the specific energy absorption indices of the structural components. The new procedure allowed for standard state-space formulation of the crash problem. The performance of the new simulation approach is tested for a typical vehicle structure in two possible orientations called normal mode and reversed mode. The results obtained for the impact problem in normal structural mode show that a desirable energy absorption pattern of 45%, 25% and 20% of the total impact energy could be achieved through plastic deformation of the front frame, sheet metal and torque box respectively. Testing the impact system in reversed structural mode results in a rather poor energy absorption pattern in which 2.5%, 50% and 43% of the total impact energy were absorbed through deformation of the front frame, sheet metal and torque box respectively, showing that unreasonably high percentage of the total impact energy is transmitted to the interior structures. The effort to quantify the energy absorbed by major vehicle front structure in both desirable and undesirable crash responses, and the computational efficiency achieved through the present method could help to enhance decision process during assessment of the components or prototype. It is found that good crash performance may be guaranteed by ensuring sufficiently high (up to 65%) contribution to the energy absorption scheme through the deformation of the foremost structures which includes the front frame and the sheet metal.

Vehicle Front Structure Energy Absorbing Optimization in Frontal Impact

Energy absorption performance is one of the most important indexes in the vehicle safety during impact. Research on the car frontal structure energy performance and structure optimization was conducted in this paper. Whole vehicle model was established by HyperMesh and simulated in LS-DYNA. Simulation results indicated that modification was needed for the original structure to meet the industry requirements. Based on simplified whole vehicle model, orthogonal design optimization was implemented, including bumper cross beam material (A), bumper cross beam thickness (B), energy absorber groove distance (C), and front longitudinal beam groove number (D), with 3 levels for each factor. The best option was B3D1A3C3 which was gained by using range analysis and integrated balance method. Simulation results showed that both front and total energy absorptions were improved. The optimized structure increased front energy absorption to 51.1%, which can meet the industry requirement.

Effects of ground impact on traumatic brain injury in a fender vault pedestrian crash

The present study replicated a series of vehicle–to–pedestrian crashes involved in a right–corner frontal impact up to a secondary or ground impact. The results showed that post–impact pedestrian kinematics and subsequent kinetics are not easily predictable and are considerably affected by the vehicle front structure and impact speed. The Head Injury Criterion (HIC), calculated with a resultant linear acceleration of the head, reached around 1000 or higher because of secondary head strike even at 25 km/h. Similarly, the maximum rotational acceleration of the head resulted in higher values owing to ground impact rather than primary head strike. This study has also suggested the importance of accounting for both linear and angular acceleration pulses applied to the head to assess the potential risk of sustaining Traumatic Brain Injury (TBI) due to eventual contact with the ground even at low impact speeds, and this should be a focus of future research.

Identifying Key Parameters for Design Improvement in High-Dimensional Systems With Uncertainty

Key parameters may be used to turn a bad design into a good design with comparatively little effort. The proposed method identifies key parameters in high-dimensional nonlinear systems that are subject to uncertainty. A numerical optimization algorithm seeks a solution space on which all designs are good, that is, they satisfy a specified design criterion. The solution space is box-shaped and provides target intervals for each parameter. A bad design may be turned into a good design by moving its key parameters into their target intervals. The solution space is computed so as to minimize the effort for design work: its shape is controlled by particular constraints such that it can be reached by changing only a small number of key parameters. Wide target intervals provide tolerance against uncertainty, which is naturally present in a design process, when design parameters are unknown or cannot be controlled exactly. In a simple two-dimensional example problem, the accuracy of the algorithm is demonstrated. In a high-dimensional vehicle crash design problem, an underperforming vehicle front structure is improved by identifying and appropriately changing a relevant key parameter.

A new approach for optimizing automotive crashworthiness: concurrent usage of ANFIS and Taguchi method

Design optimization is presented for the crashworthiness improvement of an automotive body structure. The optimization objective was to improve automotive crashworthiness conditions according to the defined criterion (occupant chest deceleration) during a full frontal impact. The controllable factors used in this study consisted of six internal parts of the vehicle's frontal structure in a condition that their thickness was the "design parameter". First using the Taguchi method, this study analyzed the optimum conditions in discontinuous design area and impact factors and their optimal levels of design objectives were obtained by analyzing the experimental results. Next to model a precise understanding of the explicit mathematical input---output relationship, fuzzy logic is utilized which make use of full factorial design set of experimental test cases resulted from Taguchi predicting formulations. Interestingly, the optimum conditions for automotive crashworthiness occurred with 2.72 % improvement in the defined crashworthiness criterion in comparison with the baseline design while selected structural parts experienced mass reduction by 8.23 %.

Peeling of Aluminium Tubes as an Efficient Method for Energy Absorption in Vehicle Front Structures

Current crash structures in cars are still using the buckling of metallic structures to absorb the kinetic energy in case of an impact. The disadvantage of this technology is that changes within the static structural behaviour, like e.g. the stiffness or eigenfrequencies, will cause changes in the crash behaviour, even if this is not desired. This correlation between static and dynamic behaviour causes many development loops to adjust the crash behaviour, e.g. through optimizing trigger geometries which lower the initial crash forces. The German Aerospace Center (DLR) - Institute of Vehicle Concepts has developed a novel method to offer an efficient way of absorbing energy by peeling the outer skin of load bearing structures, like the crash boxes and the longitudinal rails. This technology provides an adjustable force level without changing the static behaviour of the front structure itself. This property offers the opportunity to create adaptable crash behaviour with only smallest changes within the peeling depth. Furthermore, it is possible to generate close to ideal force-deflection curves, which offers the potential to achieve high specific energy absorption. The DLR will show results of static and dynamic testing of crash tubes and of a vehicle front structure equipped with this mechanism. In addition the implementation of the methodology into the dynamic simulation with LS-Dyna will be shown. Benefits and limitations of this novel energy absorption method will be discussed.

Front Rail Crashworthiness Design for Front Oblique Impact Using a Magic Cube Approach

The front rail, as one main energy absorption component of vehicle front structures, should present steady progressive collapse along its axis and avoid bending collapse during the front oblique impact, but when the angle of loading direction is larger than some critical angle, it will appear bending collapse causing reduced capability of crash energy absorption. This paper is concerned with crashworthiness design of the front rail on a vehicle chassis frame structure considering uncertain crash directions. The objective is to improve the crash direction adaptability of the front rail, without deteriorating the vehicle's crashworthiness performance. Magic Cube (MQ) approach, a systematic design approach, is conducted to analyze the design problem. By applying Space Decomposition of MQ, an equivalent model of the vehicle chassis frame is generated, which simplifies the design problem. Based on this model, a two-layered front rail is proposed using a multi-step multi-domain topology optimization method and a response surface method. Numerical simulations are carried out with Altair/Hypermesh and LS-DYNA to compare the crashworthiness performances of the original front rail and the proposed two-layered design. The result shows that the two-layered front rail, with a reduced weight by 17%, can absorb 46% more energy in the 30 degree front impact than the original design, meanwhile, the proposed design eliminates the bending collapse on its rear end when the angle of loading direction reaches the critical angle. The energy absorption capability and the direction uncertainty adaptability of the front rail are significantly improved. Language: en

Improve Lower Leg Impact Performance Considering Pedestrian Protection

To improve the lower leg impact performance of the vehicle bumper in the collision of vehicle to pedestrian, the finite element (FE) model of a vehicle front structure was developed, and correlated with the test results. The lower legform impactor FE model was used to investigate the performance of the vehicle bumper at different structure conditions. It was finally determined that vehicle to lower legform impact performance can be improved by reducing the energy absorbing foam stiffness and modifying the bumper bracket structure to enlarge the collapse space.

Reliability-Based Multiobjective Design Optimization under Interval Uncertainty

This paper studies the reliability-based multiobjective optimization by using a new interval strategy to model uncertain parameters. A new satisfac- tion degree of interval, which is significantly extended from (0, 1) to (-¥, +¥), is introduced into the non-probabilistic reliability-based optimization. Based on a predefined satisfaction degree level, the uncertain constraints can be effectively transformed into deterministic ones. The interval number programming method is applied to change each uncertain objective function to a deterministic two-objective optimization. So in this way the uncertain multiobjective optimization problem is transformed into a deterministic optimization problem and a reliability-based multi- objective optimization is then established. For sophisticated engineering problems, the objectives and constraints are modeled by using the response surface (RS) ap- proximation method to improve the optimization efficiency. Thus the reliability- based multiobjective optimization is combined with the RS approximation models to form an approximation optimization problem. For the multiobjective optimiza- tion, the Pareto sets can be obtained with different satisfactory degree levels. Two numerical examples and one real-world crashworthiness design for vehicle frontal structure are presented to demonstrate the effectiveness of the proposed approach.