Mathematical modeling and optimization of a vehicle crash test based on a single-mass

Klausen, Andreas; Tørdal, Sondre Sanden; Karimi, Hamid Reza; Robbersmyr, Kjell G.; Jecmenica, Mladen; Melteig, Ole

doi:10.1109/wcica.2014.7053313

Cited by 8 publications

(7 citation statements)

References 5 publications

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“…In recent years, the explicit non-linear finite element analysis (FEA) has emerged as, undoubtedly, the most widely renowned modelling approach in EV crashworthiness due to its high accuracy in material specifications, stresses, and deformation during the impact [73]. The aspects of analyses include the structural behavior of the vehicle and mechanisms for protecting against high-voltage.…”

Section: Recent Research On Crashworthiness Of Evsmentioning

confidence: 99%

Lessons from the Electric Vehicle Crashworthiness Leading to Battery Fire

Chombo

Laoonual

2021

Energies

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Electric vehicles (EVs) are currently emerging as alternative vehicles due to their high energy efficiency and low emissions during driving. However, regarding the raising concern, the safety of EVs can further be improved before they completely replace conventional vehicles. This paper focuses on reviewing the safety requirements of EVs, especially those powered by Li-ion battery, based on the mechanical abuse tests from the international standards, national standards, regulations and other laboratories standards, and safety of occupants from the regulations and safety programs. Moreover, the publicly reported real-world fire incidents of EVs based on road crashes were collected and reviewed. The objective is to highlight the gap and challenges arose between the current safety requirements and real-world fire incidents of EVs and provide the way for assisting the future research in the area of EV safety, particularly light duty passenger vehicle. The serious challenges observed include high impact speed, multi-crashes per incident, multiple barriers of different types involved in the accident, and post-crash safety (serious injury and demise) of occupants and rescue teams. While addressing these challenges, this review will aid researchers and manufacturers working in batteries, EVs, and fire safety engineering to narrow the gap and enhance the safety of future EVs in areas of battery materials, fire extinguishing, and vehicle’s body structure.

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Section: Recent Research On Crashworthiness Of Evsmentioning

confidence: 99%

Lessons from the Electric Vehicle Crashworthiness Leading to Battery Fire

Chombo

Laoonual

2021

Energies

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“…Different forms are configured and used in analyzing the crash response. For instance, the basic lumped mass model consists of masses and linear springs [1], LPM including beam elements, plastic hinges, nonlinear contact spring elements, and rigid solids [2], and models using nonlinear spring and damper [3,4]. However, considering the mathematical complexity of a crash event representation, it was concluded that the determination of the force elements in the mathematical model has a remarkable influence on response prediction [5][6][7][8].…”

Section: Introductionmentioning

confidence: 99%

Optimization Design on Functionally Graded Cem for Trains Based on LPM Model with Calibrated Parameters

Chen

2020

Shock and Vibration

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Lumped parameter modeling (LPM) combined with optimization techniques is an efficient approach for parametric configuration design of energy absorption to improve crashworthiness performance during train collision. This work proposed a simplified model by introducing a bar element to consider the influence of the carbody in a collision process. The optimization method is applied to calibrate the equivalent parameters of the bar element. Bar elements with calibrated parameters are adopted in establishing a one-dimensional (1D) model for the train crash. Subsequently, a novel crash energy management (CEM) mode with functionally graded energy (FGE) configuration is introduced to the train crash model for improving crashworthiness performance. The influence of parameters in graded function on interfacial force and peak acceleration is investigated and optimal design parameters are obtained by Nondominated Sorting Genetic Algorithm (NSGA-II). It is concluded that considering the behavior of the carbody can improve the accuracy of LPM in predicting the longitudinal response, and the gradient CEM is a potential energy configuration mode to improve the crashworthiness of the train in a collision.

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“…In [9], the authors proposed an approach to control the seat belt restraint system force during a frontal crash to reduce thoracic injury. Klausen et al [10,11] introduced a firefly optimisation method to estimate parameters of vehicle crash test based on a single mass-spring-damper model. Ofochebe et al [12] studied the performance of a vehicle front structure using a 5-DOF lumped mass-spring model composed of body, engine, the cross-member, the suspension, and the bumper masses.…”

Section: Introductionmentioning

confidence: 99%

“…Although LPMs have been extensively used for reconstruction of crash scenario at specific impact velocity, it is still worthy to explore more the use of LPM, for predicting the crash event at various impact velocities as a complement to the existing results e.g., in [11,33,34]. In this paper, the authors investigate whether it is possible to accurately estimate the basic crashworthiness parameters such as maximum dynamic crush and ASI, using the earlier proposed LPM [13,14].…”

Section: Introductionmentioning

confidence: 99%

Prediction of Vehicle Crashworthiness Parameters Using Piecewise Lumped Parameters and Finite Element Models

Munyazikwiye

Vysochinskiy

Robbersmyr

et al. 2018

Designs

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Estimating the vehicle crashworthiness experimentally is expensive and time-consuming. For these reasons, different modelling approaches are utilised to predict the vehicle behaviour and reduce the need for full-scale crash testing. The earlier numerical methods used for vehicle crashworthiness analysis were based on the use of lumped parameters models (LPM), a combination of masses and nonlinear springs interconnected in various configurations. Nowadays, the explicit nonlinear finite element analysis (FEA) is probably the most widely recognised modelling technique. Although informative, finite element models (FEM) of vehicle crash are expensive both in terms of man-hours put into assembling the model and related computational costs. A simpler analytical tool for preliminary analysis of vehicle crashworthiness could greatly assist the modelling and save time. In this paper, the authors investigate whether a simple piecewise LPM can serve as such a tool. The model is first calibrated at an impact velocity of 56 km/h. After the calibration, the LPM is applied to a range of velocities (40, 48, 64 and 72 km/h) and the crashworthiness parameters such as the acceleration severity index (ASI) and the maximum dynamic crush are calculated. The predictions for crashworthiness parameters from the LPM are then compared with the same predictions from the FEA.

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Mathematical modeling and optimization of a vehicle crash test based on a single-mass

Cited by 8 publications

References 5 publications

Lessons from the Electric Vehicle Crashworthiness Leading to Battery Fire

Lessons from the Electric Vehicle Crashworthiness Leading to Battery Fire

Optimization Design on Functionally Graded Cem for Trains Based on LPM Model with Calibrated Parameters

Prediction of Vehicle Crashworthiness Parameters Using Piecewise Lumped Parameters and Finite Element Models

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