The drop impact test and dynamic stability test of the custom-fit user centred bicycle helmet using Finite Element Analysis

摘要

The current sizing of a bicycle helmet is available to cater for the general head sizes, ranging from S/M and L/XL, but there is also a universal model that can fit all sizes through adjustable helmet straps. However, based on the reported human anthropometric data, the human head shape and dimensions are different according to ethnic group, age and gender [1-3]. Furthermore, numerous surveys addressed the discomfort in wearing a helmet, and the current sizing did not accommodate the range users [4-7]. Asian users also reported they were experiencing poor fit when wearing a helmet because most helmets are designed according to the size of Western heads [2, 8]. Therefore, it can be concluded that the general size of helmets currently available in the market could not accommodate the range of human head shapes and dimensions. One possible solution to overcome the helmet “fit” problem for each user is the customized “user-centred” or “subject-specific” helmet design approach. The key to facilitating this approach to bicycle helmet is to build the inner liner according to the contour and shape of the head of each person. However, it is also important to note that changing the liner thickness and shape to improve helmet fit might influence the safety aspects of the bicycle helmet, such as the helmet liner impact attenuation properties and helmet dynamic stability. Since the user-centred design approach is quite new and has not been adopted previously in the bicycle helmet design, there is a lack of information on this area in the literature. This has motivated the author to bridge the knowledge gap, and therefore the primary aim of this research is to investigate the safety performance of a user-centred helmet liner design in drop impact test and dynamic stability test. The tests were performed using validated finite element (FE) models specifically developed for each test. In the end, a new framework was developed to test and validate the mass customised system of a new automated user-centred bicycle helmet design. Apart from its primary function as a protective item, impact strength is one of the most important aspects to be considered when designing a bicycle helmet [9]. The author has performed experimental drop impact tests on three commercial helmet models to gather important information to develop an FE model of the drop impact test. The author has also used new correlation methods, specifically created for the helmet impact test, to validate the simulation model according to the experimental results. The correlation methods are the Peak Score (PS), the Impact Duration Score (IDS) and the statistical Pearson correlation score. Very good correlation scores (more than 80%, in the scale of 0%-100%) between experimental and simulation results have been achieved using the aforementioned methods, and this indicates that the simulation model is consistent, accurate and reliable. Another important criterion for the bicycle helmet is the dynamic stability performance. The degree of helmet rotation, usually called the roll-off angle is observed, and the helmet will fail the test if the helmet completely comes of the head form. From the literature review, it was found that a very limited FE model has been previously developed to simulate dynamic stability test of a bicycle helmet. To fill the knowledge gap, a dynamic stability FE model was developed using rotational velocity as the input load to the helmet assembly. Again, the author has performed experimental dynamic stability tests on commercial bicycle helmets using a test rig specifically constructed for that purpose. The FE helmet model was observed to move and roll on the headform, similar to the helmet movement and behaviour recorded in the experiment. The Roll-off Score (RoS) results also showed that the FE model achieved comparably very similar results to those from the experiment. It should also be noted that a high-accuracy 3D (45μm accuracy) scanner was used to capture an accurate 3D representation of bicycle helmet components for both FE models. Another high-accuracy portable scanner (resolution up to 0.5mm, accuracy up to 0.1mm) was also used to scan the head shapes of participants in this study to create the customized user-centred bicycle helmet. The author also used the developed FE models to compare the performance of the user-centred bicycle helmet with the current helmet model in the drop impact tests and dynamic stability tests. Geomagic Studio 12 software was used to create the user-centred bicycle helmet based on the original commercial bicycle helmet design, where the inside part of the helmet was modified to follow the scanned head shape and size of participants, while the outside part of the helmet remained unchanged. This comparison has not been published in the literature before, and therefore it is a significant new knowledge. The result revealed that the user-centred bicycle helmet design influences the peak linear acceleration (PLA) of a helmet in an impact test. Due to the different head shape of each participant, it was observed that PLA increased when liner thickness is reduced at certain test area and decreased when liner thickness is increased. This information is important when designing the framework of customization of user-centred bicycle helmet design to make sure each user-centred helmet would pass the test without testing each of this custom helmet every time. It was also revealed that the rate of increase of the PLA is different according to the impact location when different liner thicknesses of the same helmet model were tested and compared. Moreover, foam density also influences the PLA, and higher PLA was noticed when the foam is either too hard (high-density) or too soft (low-density). A ranking of design factor influences on drop impact performance has also been established. The helmet liner thickness was found to have the most influence on impact properties of a bicycle helmet, followed by the impact location and liner density. In a dynamic stability test, the user-centred helmet was found to have a lower roll-off angle and hence performed better than the original helmet, when tested using the customised headform, made according to the head shape of each participant. This significant result strongly suggests that helmet fit improves the dynamic stability of bicycle helmet. It was also revealed that helmet dynamic stability performance was not strongly influenced by the helmet liner density because only a small difference in roll-off angles wasobserved for each helmet with different density. Conversely, dynamic stability was heavily influenced by the thickness of the liner. A helmet with thicker liner recorded a higher roll-off angle compared to one with a thinner liner. The fit of a user-centred helmet based on the commercial helmet model was compared to the original model with the standard sizing using Helmet Fit Index (HFI), using the standoff distance between the helmet and the head, as well as the helmet protection proportion. As expected, they have higher HFI than the original helmet with the standard size, indicating that the user-centred helmet has a better fit with the participant head shape compared to the helmet with the standard sizes. A new automated and customised bicycle helmet design has been developed within the research group. Using this tool, a customised bicycle helmet is developed using the digital data of head scan of an individual. For certification and testing purpose, the system created four headform groups based on the 122 participants of a cyclist community in Australia. A novel approach to creating the Maximum Head Shape (MaH) and Minimum Head Shape (MiH) of each group was proposed to test the new helmet design in a drop impact test and dynamic stability test. The worst-case helmet is created based on the Maximum Head Shape (MaH), while the best-case helmet is created using the Minimum Head Shape (MiH) of the group. This method was adopted in a case study of only a group, and we could ensure that each customised helmet design in that group would pass the drop impact test and dynamic stability test. The methods of using best-case and worst-case helmets as limitation eliminate the necessity to test each customised helmet created based on the head shape of the participant.