Transport of liquid water is one of the basic producer requirements to ensure the suitable physiological comfort of drivers. This paper deals with the investigation of car seat covers’ efficiency from the point of view of their moisture management. Two methods were used for the evaluation of moisture transport in the car seat cover structures. Both of them use a thermography system for water transport detection. The first method evaluates dynamic water spreading in cross-section in the frontal plane; the second one examines horizontally dynamic spreading of liquid drops on the upper face of the sample. The tested materials were designed to understand the role of the middle layer of textile sandwich car seats in their moisture management behavior. The same PES woven structure in the top layer was used for all tested samples. Knitted spacer fabric (3D spacer fabric), polyurethane foam, and nonwoven were used as padding in the middle layer in car seat covers. In summary, the distribution and transport of liquid moisture in a sandwich structure are fundamentally affected by the middle layer of composite, especially by material composition and the value of porosity. The best results were shown in 3D spacer fabric for car seat covers.
Keywords
- Moisture management
- car seat
- thermography
- cross-section
- knitted spacer fabric
To date, a lot of research work has been done on the comfort of automotive seating [1, 2]. Car seat covers often consist of several layers of different materials, usually polyester fabric, leather, or synthetic leather laminated to a polyurethane foam (PU foam), knitted spacer fabric (3D spacer), or nonwoven. Car producers increasingly place an emphasis on the heat and moisture transport properties of car seat covers to ensure the physiological comfort of drivers. Moisture management behavior, thermal properties, and air transport of 3D spacer and PU foam, which are commonly used as padding in car seat covers, have been examined [2,3,4,5,6]. Researchers cannot agree on whether it is better to use PU foam or 3D spacer as the middle part of the car seat cover. One group of researchers prefer polyethylene terephthalate (PET) fibers for automotive application (both for top and middle layers), due to their excellent properties, like high tenacity; resistance to abrasion, light, heat, and chemical aging; UV resistance; dimensional stability; recyclability; etc. [5, 7, 8]. Others are in favour of modified PU foam in the middle layer because of its excellent elasticity and perfect recovery from compression [8]. Generally, moisture management of fabrics is mainly influenced by the fiber type, yarn construction, and fabric construction [9, 10]. The flow of liquid in fiber assemblies, such as yarn and fabric, mainly happens due to capillary forces [11, 12]. This capillary force depends on the radius of the capillary channel and the contact angle between the liquid and capillary channel, as well as the rheological properties of the liquid [13]. Wicking methods are well-known methods that use the capillary phenomenon to evaluate the liquid transport properties of fabrics. The rate (distance per unit of time) of liquid travel along and/or through a fabric specimen is visually observed according to a standardized wicking method, and manually timed and recorded at specific intervals [14]. Interest in 3D spacer is becoming more and more prevalent in all areas. Research is underway on water absorption in 3D spacer fabrics of various thicknesses [15,16,17].
In the present work, a technique based on the combination of the thermography system and image analysis system was developed. The thermography system takes advantage of a physical rule: during water evaporation, heat rises. This process can be captured on a thermograph by a thermography system. The thermographs obtained are evaluated by an image analysis system and software MATLAB to find moisture management parameters of the textile sandwich.
Three sets of sandwich fabrics frequently used in the production of car seat covers were evaluated in the study. It was interesting to determine how different structures in the middle layer of car seat covers (3D spacer, PU foam, and nonwoven) affect liquid moisture transport (Figure 1). The top layer was the same for all tested samples (Figure 2). The essential characteristics of all tested car seat fabrics are shown in Table 1. All layers of the sandwiches were connected by the technology intended for the given type of sandwich.
Figure 1
3D structure image of sandwich fabrics by microtomography system SkyScan 1272. Sandwich structure – the same top layer and different second layer: (a) 3D spacer, (b) PU foam, (c) nonwoven padding

Figure 2
Top layer of sandwich – details of woven fabric: (a) satin weave, (b) pattern draft, (c) hollow fiber

Specification of the tested samples S1, S2, S3
Code - structure | Fiber content | Pattern | Fineness [dtex] | Thickness [mm] | Weight [g/m2] | |
---|---|---|---|---|---|---|
Top layer | woven fabric | 100% PES Hollow Fiber | satin | 400 | 0.73 | 204 |
Sample code - structure | Fiber content | Type of connection with top layer | Thickness [mm] | Weight [g/m2] | ||
Second layer | S1 – knitted spacer fabric | 100% PES | Hot melt gluing | 4.9 | 335 | |
S2 – foam + weft knitted fabric | 100% PUR+100%PES | Flame lamination (all layers) | 6.7 | 226 | ||
S3 – nonwoven | 70%PES/30%WO | Powder lamination | 4.4 | 230 |
The liquid moisture transport of the sandwich fabrics was investigated in two ways:
dynamic water spreading in cross-section in the frontal plane of sample (hereinafter referred to as “cross-section”) dynamic water spreading in horizontal plane of sample, on the upper face (hereinafter referred to as “face “)
Both use a thermography system for water transport detection and an image analysis system. The use of infrared cameras for monitoring the spread of liquid in the fabric is possible thanks to the visibility of physical phenomena in infrared spectrum wavelengths. Based on the principles of electromagnetic wave motion, a thermography camera is used to represent material characteristics in infra-red wavelengths. The method allows for non-contact, rapid, and continuous measurements. The results of the above-mentioned methods were monitored and discussed in order to detect the real behavior of tested sandwich fabrics during liquid transport within their structure. The output from thermal imaging cameras—the thermograph—was processed using a script created in the MATLAB program. The original thermograph was converted to a binary image before calculating the area, as shown in Figure 3. The tested sandwiches were laid on foam, which corresponds to the next standard layer of the car seat in practical use.
Figure 3
The original thermographic image of the distribution of the liquid: (a) thermographic image detail of cross-section, (b) prepared binary image for script of MATLAB

Figure 4 represents the measuring device assembly of the methods above. Two thermography systems simultaneously recorded the spreading of a liquid drop after the application of the liquid on the edge of the sample. The result is an image of the moisture border on the face side of the top layer sample and a picture of the profile sample with its sandwich structure.
Figure 4
Schematic diagram: measuring device assembly.

Drops were applied using the FB32266 digital micropipette with volume 70μl. The experiment allows monitoring of how fast material can absorb the liquid and the transmission of the moisture from the top layer of the sample to the next layers in real-time. All the statistical computations were performed from ten measurements.
The experiment took place in a dark measurement chamber with dimensions of 130 × 100 × 155 cm. All processes were automated to eliminate external environmental influences and to ensure stable conditions. The experiment builds on previous research by the authors and expands the use of non-contact methodology [14].
These characteristics were evaluated from the image analysis system:
wetted area wetted area
The results of wetting the sandwich may indicate how fast the sandwich can absorb and spread liquid moisture in three dimensions. Wetting speed could be an essential criterion in selection of materials for the given purpose.
Thermographic records of the measurements were evaluated using the ThermaCAM Researcher Professional program. Video frame rate was set to one frame per second. The calculation of the size of the measured area was determined using a script of MATLAB. The measured values showed average area values (mm2) of ten measurements of a particular sandwich fabric (S1, S2, S3). The results of the wetting process were manifested by the various liquid moisture spread sizes of the wetted area and water distribution in the structure, depending on the type of fabric in the second layer of the sandwich. To ensure control of the dripping of the entire volume of water, each sample was weighed on digital analytical balances.
The analysis of recorded thermographs enables the evaluation of the area and shape of the area wetted by a drop of water. Figure 5 illustrates the results of the spread of liquid moisture in a time of 350 seconds in the cross-section of the sandwich. There are shape and area differences in the wetted area according to different sandwich structure.
Figure 5
Thermograms - wetted area in cross-section of a sandwich in a time of 350 seconds: (a) knitted spacer fabric – sample S1, (b) PU foam – sample S2, (c) nonwoven padding – sample S3

A representative thermogram was evaluated every 50 seconds. All the statistical computations were performed from ten measurements, as seen in Table 2.
Detailed parameters of dynamic water spreading
mean | 222.6 | 316 | 354 | 399.2 | 439.8 | 465.8 | 493.2 | |
st. deviation | 16.7 | 23.9 | 33.3 | 29.8 | 30.1 | 31.3 | 46.7 | |
mean | 50.1 | 85.7 | 117.5 | 145.8 | 171.0 | 195.5 | 217.6 | |
st. deviation | 3.6 | 11 | 11.5 | 13.2 | 12.9 | 15.8 | 18.5 | |
mean | 24 | 54.6 | 88.8 | 97.6 | 118.8 | 137.0 | 163.1 | |
st. deviation | 2.9 | 7.5 | 14.6 | 13.1 | 15.0 | 18.2 | 17.7 | |
mean | 245.0 | 330.7 | 358.8 | 381.7 | 401.9 | 405.2 | 419.2 | |
st. deviation | 25.5 | 36.5 | 37.6 | 32.5 | 42.6 | 49.7 | 39.6 | |
mean | 39.3 | 75.8 | 104.7 | 111.0 | 126.9 | 139.0 | 152.1 | |
st. deviation | 3.3 | 8.6 | 8.1 | 9.2 | 13.4 | 17.4 | 14.6 | |
mean | 20.9 | 58.5 | 78.9 | 87.9 | 97.2 | 108.7 | 121.6 | |
st. deviation | 2.1 | 7.4 | 14.1 | 10.9 | 12.4 | 13.1 | 14.5 |
As shown in Figure 6, the liquid spread the fastest in the sandwich containing a 3D spacer (S1). In this type of sandwich, the wetted part occupied the largest area compared to S2 and S3. The liquid applied to the sandwich samples containing PU foam (S2) or nonwoven (S3) were absorbed at a constant rate. The wetted part on these types of sandwich fabric occupied a smaller area on average compared to samples with 3D spacer.
Figure 6
Moisture transport – cross-section

The results of wetting the fabric on the face side indicate how fast the fabric can absorb and spread liquid moisture on its surface. Although the first layer of sandwiches is identical, dynamic water spreading on the face side of the sandwiches S1, S2, and S3 is different, as seen in Figure 7.
Figure 7
Thermogram showing a liquid in on the surface of a sandwich fabric in a time of 350 seconds: (a) knitted spacer fabric – sample S1-face, (b) PU foam – sample S2-face, (c) nonwoven padding – sample S3-face

Again, it turns out that sample S1 is clearly different, as seen in Figure 8.
Figure 8
Moisture transport – face side of fabric

The method allows the simultaneous checking of the spreading of a liquid drop from two views after the application of the liquid on the edge of the sample. The textile sandwich is in its essence a difficult structure, the properties of which under the first layer can only be predicted. The concept of the experiment is to evaluate and find a correlation between moisture transport on the face side of the sample and dynamic spreading in the cross-section. The wetted area of samples (S1, S2, S3) are different in size and shape which could be due to the uneven distribution of intercapillary spaces in each individual type of sandwich material and also the method of joining the individual layers in these sandwich structures.
In the mutual comparison of individual samples, the trend of wettability from both camera views in time 0 – 150 seconds is the same The comparison of moisture transport in cross-section and in face of knitted spacer fabric seen in sample S1, can be seen in Figure 9. The wettability trend behaves in the same way between cross-section and face for the sample S2 and between the cross-section and face for the sample S3, as seen in Figure 10, 11. 150 seconds is a turning point. From this moment the curves of individual samples start to behave differently. However, their expression is not significant in terms of remaining wettability. We could argue that only one view (for example, S1 or S1-face) would be sufficient to make a crucial decision on how the sandwich will behave.
Figure 9
Comparison moisture transport – cross-section and face of knitted spacer fabric

Figure 10
Comparison moisture transport – cross-section and face of PU foam

Figure 11
Comparison moisture transport – cross-section and face of nonwoven padding

The summary of the results from both cameras clearly indicates the excellent ability to transport liquid in a sandwich structure using a knitted spacer fabric. It can be assumed that the liquid from sandwich type S1 should evaporated the fastest, as it was spread over a large area of both the monitored sides.
The slope is one of the essential characteristics of a line and helps us measure the rate of change. If we want to use the results of the experiment, the expression of the rate of change along the regression line offers itself. The whole phenomenon can be divided into two parts. The first part is defined as start transport of moisture through sandwich. The following observed parts of the curve we can call the running-in phase. The slope of the curve in the initial phase is crucial for the interpretation of the ability of the sandwich in terms of moisture transfer.
The equation for the slope of the regression line is:
The knitted spacer fabric (S1) shows a logarithmic course of the curve, the others (S2, S3) linear, see Figure 6, 8. Table 3 presents the course of moisture transport in terms of the slope according to the equation (1) in three phases, illustrated in the Figures 9–11. The first phase of 0–50 seconds is the decisive onset of wettability of the sandwich. We can consider it as the time zone of the greatest interest. The second phase of 50–150 seconds indicates the saturation rate of the sandwich. The last phase of 150–350 seconds is the running phase of liquid penetration. It is certainly the most important phase of the first phase, and it is for it that we want to set some kind of boundaries for sandwich differentiation.
Wettability trend – slope
4.45 | 4.90 | 1.00 | 0.79 | 0.48 | 0.42 | |
1.31 | 1.14 | 0.68 | 0.65 | 0.65 | 0.58 | |
0.69 | 0.29 | 0.50 | 0.25 | 0.38 | 0.21 |
We can interpret our resolution as follows:
if values b ≥ 4 we affirm that moisture transport is excellent if values b = (1,4) we affirm that moisture transport is standard if values b ≤ (0,0.5) we affirm that moisture transport is slow
The new measurement method clearly showed how three different sandwiches behave despite having the same purpose of use in practice. The experimental results set boundaries for sandwiches that define excellent liquid transport and slow transport. When deciding to use different types of spacer fabric, we can expect the speed of liquid transport and orient ourselves according to the trend of the slope of the curve.
The results of wetting the sandwich may indicate how fast the sandwich can absorb and spread liquid moisture in three dimensions. Wetting speed could be an essential criterion in selection of materials for the given purpose. The influence of the type of sandwich on the wetting process is evident. Values show that the structures with higher porosity absorb more water than structures with lower porosity. The distribution and transport of liquid moisture in a composite structure are fundamentally affected by the second layer of composite its material composition, the method of joining the first and second layers and type of structure. A comparison of the results of the two views on the sandwich showed that to simplify the measurement, only one view could be used to quickly determine the wetting rate. Further research and measurements could confirm this theory. Future research would enable concentration on the investigation of moisture monitoring, but the opposite property - drying the sandwich out.
Figure 1

Figure 2

Figure 3

Figure 4

Figure 5

Figure 6

Figure 7

Figure 8

Figure 9

Figure 10

Figure 11

Detailed parameters of dynamic water spreading
mean | 222.6 | 316 | 354 | 399.2 | 439.8 | 465.8 | 493.2 | |
st. deviation | 16.7 | 23.9 | 33.3 | 29.8 | 30.1 | 31.3 | 46.7 | |
mean | 50.1 | 85.7 | 117.5 | 145.8 | 171.0 | 195.5 | 217.6 | |
st. deviation | 3.6 | 11 | 11.5 | 13.2 | 12.9 | 15.8 | 18.5 | |
mean | 24 | 54.6 | 88.8 | 97.6 | 118.8 | 137.0 | 163.1 | |
st. deviation | 2.9 | 7.5 | 14.6 | 13.1 | 15.0 | 18.2 | 17.7 | |
mean | 245.0 | 330.7 | 358.8 | 381.7 | 401.9 | 405.2 | 419.2 | |
st. deviation | 25.5 | 36.5 | 37.6 | 32.5 | 42.6 | 49.7 | 39.6 | |
mean | 39.3 | 75.8 | 104.7 | 111.0 | 126.9 | 139.0 | 152.1 | |
st. deviation | 3.3 | 8.6 | 8.1 | 9.2 | 13.4 | 17.4 | 14.6 | |
mean | 20.9 | 58.5 | 78.9 | 87.9 | 97.2 | 108.7 | 121.6 | |
st. deviation | 2.1 | 7.4 | 14.1 | 10.9 | 12.4 | 13.1 | 14.5 |
Specification of the tested samples S1, S2, S3
Code - structure | Fiber content | Pattern | Fineness [dtex] | Thickness [mm] | Weight [g/m2] | |
---|---|---|---|---|---|---|
Top layer | woven fabric | 100% PES Hollow Fiber | satin | 400 | 0.73 | 204 |
Sample code - structure | Fiber content | Type of connection with top layer | Thickness [mm] | Weight [g/m2] | ||
Second layer | S1 – knitted spacer fabric | 100% PES | Hot melt gluing | 4.9 | 335 | |
S2 – foam + weft knitted fabric | 100% PUR+100%PES | Flame lamination (all layers) | 6.7 | 226 | ||
S3 – nonwoven | 70%PES/30%WO | Powder lamination | 4.4 | 230 |
Wettability trend – slope
4.45 | 4.90 | 1.00 | 0.79 | 0.48 | 0.42 | |
1.31 | 1.14 | 0.68 | 0.65 | 0.65 | 0.58 | |
0.69 | 0.29 | 0.50 | 0.25 | 0.38 | 0.21 |
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