Volvo Car Corporation uses nCode DesignLife to predict fatigue life performance

Fatigue life prediction is one of the most critical engineering disciplines in the automotive industry, affecting both car safety and potential warranty issues. Further, accurate fatigue life predictions support the work to reduce the weight of the car. In the past automotive manufacturers invested billions in the creation of multiple prototypes and physical testing. As technology advanced and computer-aided design and engineering tools became more robust, the car development process shifted from physical to virtual testing. This has led to lower development costs, shorter lead times, and, because more design variants can be examined in the same time frame, higher-quality cars. Key to this paradigm change in the development process is the comprehensive use of the right CAE tools early in the design process, long before the first physical prototype. A good example of successful fatigue simulation usage in the automotive development process is Volvo Car Group (Volvo Cars). Volvo Cars’ CAE teams apply technologies such as nCode DesignLife to predict the fatigue life performance of new cars.

About Volvo Cars

In production since 1927, Volvo is one of the most well-known and respected car brands in the world with car sales in around 100 countries. Volvo Cars has been under the ownership of the Zhejiang Geely Holding of China since 2010. As of December 2015, Volvo Cars had almost 29,000 employees worldwide. The company’s main office including product development, marketing, and administration functions are located in Göteborg, Sweden. A technology center is also established in Shanghai, China. The company’s main production plants are located in Göteborg, Ghent (Belgium), and Chengdu and Daqing (China), while engines are manufactured in Skövde (Sweden) and Zhangjiakou (China), and body components in Olofström (Sweden).

Fatigue life prediction at Volvo Cars

When a new car is developed, all components and assemblies have to be tested for fatigue life, first virtually and later through physical testing, to be approved for production. At Volvo Cars, the CAE analysis teams work closely with testing and design teams to keep required development iterations to a minimum.

“The most complex fatigue analysis we have is the body rig test,” says Sällström. “To physically test the body structure a complete car is taken to the test track and driven a few laps to measure accelerations and wheel forces. The car is then brought to the test rig. The loads applied in the rig are iterated until they give the same accelerations and forces as on the test track. The load cycles are then repeated to correspond to a specified number of laps on the test track.”

At the beginning of a new car development project, the durability CAE analysis team receives CAD data along with other information about the components from the design teams. With this input, the CAE engineers create a multi-body simulation model of the car, which is then analyzed on a virtual test track. The results of the multi-body analysis include time history loads at the body attachment points, which are used for the fatigue life prediction with nCode DesignLife.
During a car development project, Volvo Cars has a number of CAD model freezes, each of which is used by the CAE team to create CAE models. A dynamic finite element (FE) analysis of the car body structure is performed to find the eigenfrequencies and eigenmodes of the structure. The FE-model usually consists of around 5,000,000 elements and includes 5,000 spot welds, as well as arc welds, laser welds, weld nuts, and other connections. Body trim elements such as the radiator, seats, doors, fuel tank, etc., are also included. The eigenfrequencies and eigenmodes are needed together with the time history loads to conduct the fatigue life prediction with nCode DesignLife.

Time load history data from the test track is used to mimic the same loads on the test rig.

If the fatigue analysis indicates a place where a crack might occur, the CAE engineers give this input to the design teams. Together, design and CAE engineers discuss how to improve the body design by changing the geometry or just a radius, adding or moving spot welds, or using a different material or material thickness. If the fatigue analysis indicates very long fatigue life, this information can be used to reduce the weight of the car. nCode DesignLife offers sophisticated spot weld and seam weld analysis capabilities, which are widely used by the fatigue engineers at Volvo Cars, together with the strain life and stress life modules.

Depending on whether a new car is created on an entirely new car platform, or if an existing platform is used, the engineers might simulate hundreds of runs of the body rig during the full car development project.

This visual shows the correlation between CAE and physical testing. A fatigue crack is predicted in CAE using nCode DesignLife (left). The same fatigue crack is found in the physical correlation test (right).

Figure 1: Spiked data before (top) and after (bottom) correction

Benefits and outlook

The benefit of this approach is evident when looking at the number of physical prototype test cars needed in the development process. Ten years ago Volvo Cars would build up to four prototype cars for fatigue testing in the body rig during a car development cycle. Today this number has been reduced to one prototype car for the majority of projects. Fewer prototype cars means lower costs and a shorter, more efficient product development cycle.

With increased analyzing capability, the number of components that are evaluated for fatigue life by the CAE team has dramatically increased. As a result of CAE tools such as nCode DesignLife, many more components can be analyzed virtually in the same time frame, offering a more complete picture and an overall better quality of the car. When a physical car is finally built, the design is much more mature than in the past.

Sällström sums up the advantages of this virtual approach, saying, “With nCode DesignLife and today’s development process, we have our answers much faster than in the past, and they are more accurate. We get better designs faster, and can reduce the overall development time for the car. In addition, nCode DesignLife enables the repeatability of the process, which is very important when identifying critical areas.”

In the future, Volvo Cars’ CAE durability team expects to need even fewer physical tests, and to use those only for final validation of the CAE analyses, reducing overall lead time even more. One challenge will be finding the right balance between the speed and accuracy of the analyses, depending on how much detail is needed in each development phase. And, as the automotive industry continues its quest for lightweight cars with long fatigue life, new materials and new types of joints will provide new challenges for the CAE team. Increasing efficiency in modeling, so that the same model can be used for different analyses, will be a key to meeting these goals, and Volvo Cars’ CAE team is on this road to success.

Figure 4: Sources of noise in different frequency ranges

The first step in this process is to input the time history data into GlyphWorks using the time series input glyph. The anomaly detection algorithms within GlyphWorks are used to detect outliers. A measurement specialist reviews the anomalies and corrects spikes while keeping an eye out for other defects, such as saturation, that might require the data to be discarded.

Global statistics are then computed on each channel such as max, min, mean, standard deviation, RMS, skewness and kurtosis. These stationary test values are used to quickly assess whether the signal is centered around its mean and its peakiness. Statistical analysis is performed to determine whether the mean and standard deviation values remain constant over the sampling period. These analysis help the measurement expert determine whether to use a deterministic or probabilistic approach to calculate the fatigue damage spectrum.

Figure 5: Fatigue damage spectrum calculation with GlyphWorks

With nCode DesignLife, standard analysis processes can be saved and reused, improving consistency and quality.

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CAE-based fatigue analysis

nCode DesignLife is an up-front design tool that identifies critical locations and calculates realistic fatigue lives from leading finite element (FE) results for both metals and composites. Design engineers can go beyond performing simplified stress analysis and avoid under- or over-designing products by simulating actual loading conditions to avoid costly design changes.

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Volvo Car Corporation uses nCode DesignLife to predict fatigue life performance

About Volvo Cars

Fatigue life prediction at Volvo Cars

Benefits and outlook

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