IoT in Day-to-Day Life: Vehicle Body Fatigue Analysis

Introduction

The term fatigue in this context means the cyclic loading of material. The principle of fatigue is based on the material S-N curve, which is material strength (S) versus the number of load cycles (N). As the number of load cycles increases, the material strength weakens. A fatigue analysis is conducted to determine the durability and life of the component. A lab setup with test rigs and instrumentation is a conventional technique used for conducting fatigue analysis. In the modern world of digitization, finite element-based approaches are commonly used. The finite element approach is considered the best approach due to savings in time and resources over the conventional approach. To conduct fatigue analysis for the vehicle body using a finite element approach, the inputs from vehicle-road interaction such as vertical acceleration and number of cycles are necessary. The vehicle is instrumented with data acquisition devices and the vehicle-road response is captured. The road surface quality equally influences fatigue behaviour. If the road is rough or undulated, the vertical acceleration is more intense, which results in reduced fatigue life. If the road is good, fatigue life is longer. Vehicles travel mostly on concrete or asphalt types of roads during their life span. The seasonal changes like monsoon rains and floods spoil the road surface, and this in turn influences fatigue. Therefore, study of fatigue is necessary on type of roads intended for the design of the vehicle. The fatigue analysis is used by Original Equipment Manufacturer (OEM) for fully built bodies like cars, utility vehicles, truck cabins, and chassis whereas hardly ever used by vehicle body builders for body building applications like buses, truck load bodies, containers etc. This is due to the lack of road load input data for benchmark vehicles, the high cost of proprietary data acquisition equipment to generate own data, and time constraints for body building development activity required by customers. In the Indian market, vehicle body builders are facing stiff competition from their peers in terms of product pricing, weight, mileage, and payload carrying efficiencies. Vehicle body builders must make constant efforts on light weighting of vehicle body to gain leverage over their competitors and therefore may consider a proper analytical approach such as fatigue analysis for durability confirmation. This research study focuses on the way of capturing and recording the vehicle-road response using low-cost data acquisition methods, making it affordable for the vehicle body builders to conduct vehicle body fatigue analysis.

The data acquisition instruments are required for recording the vehicle-road response. The proprietary data acquisition instruments available on the market are expensive as they are designed for robust usage like measuring the leaf springs or vehicle axle components which have high vertical acceleration values. The vehicle body has a lower operating range of vertical acceleration as compared to vehicle components below vehicle suspension which makes it feasible to use low-cost IoT components for data acquisition. The vehicle body builders cannot afford the cost of proprietary data acquisition instrumentation. As a result, as a first step, there is a need to suggest an affordable tool for data acquisition and a method for preparing input data for fatigue analysis, which are discussed in this research study.

The main aim of this research is to propose an affordable solution to the vehicle body builders on data acquisition for vehicle body fatigue analysis. With this affordable solution, the body builders will incur low expense on the data acquisition instrument and can focus on the analysis part. The research objectives are formulated based on the aim of this study which are as follows:

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  To study the recent developments in the tools and techniques used for data acquisition of vehicle-road interaction.

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  To propose a low-cost data acquisition device using IoT for acquiring the parameters for fatigue analysis.

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  To acquire a dataset practically using the proposed data acquisition instrument.

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  To analyse the acquired dataset and prepare input test cases for fatigue analysis.

The research questions are as follows.