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Modelling Resistance Spot Welding of AHSS

Modelling Resistance Spot Welding of AHSS

Authored by Max Biegler, Research Assistant RSW, Fraunhofer IPK, Berlin

Modelling resistance spot welding can help to understand the process and drive innovation by asking the right questions and giving new viewpoints outside of limited experimental trials. The models can calculate industrial-scale automotive assemblies and allow visualization of the highly dynamic interplay between mechanical forces, electrical currents and thermal flow during welding. Applications of such models allow efficient weldability tests necessary for new material-thickness combinations, thus well-suited for applications involving Advanced High -Strength Steels (AHSS).

Virtual resistance spot weld tests can narrow down the parameter space and reduce the amount of experiments, material consumed as well as personnel- and machine- time. They can also highlight necessary process modifications, for example the greater electrode force required by AHSS, or the impact of hold times and nugget geometry. Other applications are the evaluation of whole-part distortion to ensure good part-clearance and the investigation of stress, strain and temperature as they occur during welding. This more research-focused application is useful to study phenomena arising around the weld such as the formation of unwanted phases or cracks.

Modern Finite-Element resistance spot welding models account for electric heating, mechanical forces and heat flow into the surrounding part and the electrodes. The video shows the simulated temperature in a cross-section for two 1.5 mm DP1000 sheets:

RSW Nugget Formation from worldautosteel on Vimeo.

First, the electrodes close and then heat starts to form due to the electric current flow and agglomerates over time. The dark-red area around the sheet-sheet interface represents the molten zone, where the nugget forms after cooling.While the simulated temperature field looks plausible at first glance, the question is how to make sure that the model calculates the physically correct results. To ensure that the simulation is reliable, the user needs to understand how it works and needs to validate the simulation results against experimental tests. In this text, we will discuss which inputs and tests are needed for a basic resistance spot welding model.

At the base of the simulation stands an electro-thermomechanical resistance spot welding model. Today, there are several Finite Element software producers offering pre-made models that facilitate the input and interpretation of the data. First tests in a new software should be conducted with as many known variables as possible, i.e., a commonly used material, a weld with a lot of experimental data available etc.

As first input, a reliable material data set is required for all involved sheets. The data set must include thermal conductivity and capacity, mechanical properties like Young’s modulus, tensile strength, plastic flow behavior and the thermal expansion coefficient, as well as the electrical conductivity. As the material properties change drastically with temperature, temperature dependent data is necessary at least until 800°C. For more commonly used steels, high quality data sets are usually available in the literature or in software databases. For special materials, values for a different material of the same class can be scaled to the respective strength levels. In any case, a few tests should be conducted to make sure that the given material matches the data set. The next Figure shows an exemplary material data set for a DP1000. Most of the values were measured for a DP600 and scaled, but the changes for the thermal and electrical properties within a material class are usually small.

Figure 1: Material Data set for a DP1000

Figure 1: Material Data set for a DP10001

Next, meaningful boundary conditions must be chosen and validated against experiments. These include both the electrode cooling and the electrical contact resistance. To set up the thermal flow into the electrode, temperature measurements on the surface are common. In the following picture, a measurement with thermocouples during welding and the corresponding result is shown. By adjusting the thermal boundary in the model, the simulated temperatures are adjusted until a good match between simulation and experiment is visible. This calibration needs to be conducted only once when the model is established because the thermal boundary remains relatively constant for different materials and coatings.

Figure 2: Temperature measurement with thermocouples during welding and the results. The simulated temperature development is compared to the experimental curve and can be adjusted via the boundary conditions

Figure 2: Temperature measurement with thermocouples during welding and the results. The simulated temperature development is compared to the experimental curve and can be adjusted via the boundary conditions.2

The second boundary condition is the electrical contact resistance and it is strongly dependent on the coating, the surface quality and the electrode force. It needs to be determined experimentally for every new coating and for as many material thickness combinations as possible. In the measuring protocol, a reference test eliminates the bulk material resistance and allows for the determination of the contact resistances using a µOhm-capable digital multimeter.

Finally, a metallographic cross-section shows whether the nugget size and -shape matches the experiment. The graphic shows a comparison between an actual and simulated cross section with a very small deviation of 0.5 mm in the diameter. As with the temperature measurements, a small deviation is not cause for concern. The experimental measurements also exhibit scatter, and there are a couple of simplifications in the model that will reduce the accuracy but still allow for fast calculation and good evaluation of trends.

Figure 4: Comparison of experimental and virtual cross-sections.

Figure 3: Comparison of experimental and virtual cross-sections.2

After validation, consider conducting weldability investigations with the model. Try creating virtual force / current maps and the resulting nugget diameter to generate first guesses for experimental trials. We can also gain a feeling how the quality of each weld is affected by changes in coatings or by heated electrodes when we vary the boundary conditions for contact resistance and electrode cooling. The investigation of large spot-welded assemblies is possible for part fit-up and secondary effects such as shunting. Finally, the in-depth data on temperature flow and mechanical stresses is available for research-oriented investigations, cracking and joint strength impacts.

Max Biegler
Research Assistant
Fraunhofer Institute for Production Systems and Design Technology IPK

Max Biegler (M.Sc.) finished his studies in mechanical engineering at Technical University of Munich in 2015. He is currently working as a research associate at Fraunhofer IPK in Berlin with focus on numerical modelling of welding processes.

1 C. Schwenk, FE-Simulation des Schweißverzugs laserstrahlgeschweißter dünner Bleche – Sensitivitätsanalyse durch Variation der Werkstoffkennwerte. Berlin: BAM-Dissertationsreihe, 2007.

2 J. Frei, M. Biegler, M. Rethmeier, C. Böhne, and G. Meschut, “Investigation of liquid metal embrittlement of dual phase steel joints by electro-thermomechanical spot-welding simulation,” Science and Technology of Welding and Joining, vol. 90, pp. 1–10, 2019.

Dealing with Springback: The Sidewall Curl Issue

Dealing with Springback: The Sidewall Curl Issue

Compensate or Countermeasure? Taking Sidewall Curling Seriously

In this blog post Akshay Wankhede, Application Engineer at AutoForm, describes the causes for the springback phenomenon known as the “sidewall curl”, how its occurrence on stamped panels can be identified early through simulation of full production process, and how it can be counter-measured well ahead of die tryout. Read this post to understand the challenges of the sidewall curl effect for Advanced High-Strength Steels (AHSS).

Revisiting Sidewall Curl

The issue of the sidewall curl is a common phenomenon in sheet metal stamping which is observed on the side wall of a panel, typically following the drawing operation. This distortion results in dimensional variation, creating challenges in assembly operations, affecting productivity and subsequent part quality. Naturally, it is critical that you identify the sidewall curl ahead of time to eliminate acute problems down the road. The easiest way to recognize when a sidewall curl is occurring would be to look for any progressive angle change on the sidewall or flange area as shown in Figure 1 below.

Figure 1: Obvious Occurrence Of A Side Wall Curl - Panel B

Figure 1: Obvious Occurrence Of A Side Wall Curl – Panel B

Sidewall curl issues arise as soon as the panel comes out of the tool, where it is “free” to springback. It occurs in those areas where the strain distribution is not uniform.

To better understand the sidewall curl issue, it is important to dig deeper into the basics of the cause-effect relationship of all springback phenomenon.

In general, the elastic return effect on a metal is due to the residual stress that remains after the forming forces are removed (tool opening) or after the draw panel has been trimmed.

In the sheet metal stamping process there are three main types of stresses that can be applied to a generic section of the panel: Membrane Stress, Pure Bending Stress, and Superposed Bending Stress.

1.  Membrane Stress: occurs when a specimen is uniformly stretched along its thickness beyond the elastic limit (yield point) and then allowed to relax; stresses and elastic strains are both fully released. The residual elastic strains left in the material cause the specimen to springback.

Consider the sketch in Figure 2 where the stress applied to the specimen by Force F generates a uniform stress  along the thickness s0. When the force is removed the specimen springs back by the elastic strain el. Quantitatively, the elastic return is directly proportional to the applied stress  and inversely proportional to the Young’s modulus E.

Figure 2: Typical Membrane Stress Applied During Tensile Test

Figure 2: Typical Membrane Stress Applied During Tensile Test

2.  Pure Bending Stress: commonly occurs when the sheet metal is bent over a radius (the radius of the wipe post during flanging for instance). In this case there is a large difference of stress and in strains between the outer and the inner layer of the sheet.

Let’s assume we have a flange-up operation as shown in Figure 3. If we take a look at the stress and relative strain of the layers along the thickness of the sheet, we can see that there is a neutral portion in the cross-section of the specimen that remains under “pure” elastic strain while the external and internal portions are in the plastic domain of the stress-strain curve; the inner layers are compressed (negative strain) while the outer layers have positive strain.

Figure 3: Elastic-Plastic Portion In Case Of Pure Bending Load

Figure 3: Elastic-Plastic Portion In Case Of Pure Bending Load

The layers in the elastic portion try to go back to their original length but they are unable to completely recover original shape due to the plastically deformed portion, so the final position of the sheet is the one generated by the equilibrium of these two moments. The elastic relief moment is what causes the flange to springback by a certain angle or distance, as noted in Figure 3.

3. Superposed Bending Tension: occurs when the material is stretched and bent over a radius at the same time. Because of the stretching, the strains on the inner and the outer layers are not very different and if stretched enough, they have the same direction (all strained). Therefore, when the elastic stresses are released, the residual stresses are reduced and are more uniform. In such cases, springback is more stable and produces a lower dimensional deviation (See Figure 4).

Figure 4: Superposed Bending Tension

Figure 4: Superposed Bending Tension

These conditions show that springback is caused from the strain deviation between the layers of the panel. The arising sidewall curl is a consequence of strain variation not only through the material thickness, but simultaneously along the length of the sidewall. A sidewall curl issue can also be treated as a type of springback deformation resulting from successive bending and unbending when the sheet metal is drawn over a die-radius or through a drawbead. Materials such AHSS (because of their high tensile strength) and aluminum alloys (because of their low Young’s Modulus) usually show more springback and sidewall curl problems.

Why Take Sidewall Curl Issue So Seriously?

Springback is challenging to avoid, but there are techniques that can minimize its negative effects. Other contributions in this AHSS Insights blog (see references at the end of the blog) describe using darts and beads to lock in the residual stresses and produce dimensionally accurate panels. In addition, by incorporating effective tool morphing strategies, springback can be compensated to purposefully produce dimensionally accurate panels within close tolerances. Unfortunately, sidewall curl is very difficult to fix with morphing compensation, which makes achieving a dimensionally accurate panel almost impossible to achieve. Therefore, it becomes extremely important to eliminate the sidewall curl before morphing the tools to compensate for springback during engineering prior to finishing the tools.

It is possible to examine the springback and sidewall curl risk by using simulation software tools such as AutoForm. Springback is a consequence of differences between the stresses in the layers of a sheet metal, with greater differences leading to increased sidewall curl. Evaluate bending moments in the proper orientation: If the critical radii are perpendicular to the rolling direction, then you must consider transverse properties.

Design and process changes that address springback and sidewall curl can be proven out during simulation, making it a cost-effective and efficient approach which should be incorporated into the part development process.

The Influence of Different Material and Sheet Thicknesses

Different grades do not behave the same way under all forming conditions. Higher strength of the incoming steel means higher forming tonnage, which leads to greater differences between the top and the bottom layers of the panel. This in turn leads to greater springback and in some cases greater sidewall curl. Increased thickness typically reduces both springback and curl.
The same crossmember panel shown in the pictures above has been used to investigate the effect of sidewall curl for different materials and different thicknesses. Five different materials of 1.6 mm thickness ranging from low carbon steel to high strength steel including aluminum have been used to study this effect, shown in Figure 5.

DP600 was also tested for a thicker gauge of 2.0 mm and 2.5 mm to study the effect of thickness on sidewall curl. A 5XXX series aluminum alloy is included showing the increased springback associated with the significantly lower Young’s Modulus (Elastic Modulus) characteristic of automotive aluminum alloys.

Figure 5: Springback Comparison For Different Material

Figure 5: Springback Comparison For Different Material

Springback cannot always be completely compensated; issues such as the side wall curl, oil canning, large springback magnitudes, and the lack of robustness (repeatability) need to be addressed through improvements to process and/or product. It is important to become aware as early as possible of the potential for any such issues. The earlier this awareness is achieved, the higher the chances to look for appropriate countermeasures.

Waiting to address springback and sidewall curl in tryout is a poor strategy. A thorough study of the springback phenomenon and associated conditions by simulating the full process allows for greater understanding of potential springback related challenges. The sooner potential issues are discovered, the greater likelihood that appropriate countermeasures can be successfully deployed.

To learn more about springback management, you may want to have a look at the following links:

AHSS Insights Blogs: AHSS and Springback and Managing Springback

AutoForm Blog: AutoForm’s Springback Compensation Best Practices

Akshay Wankhede AutoForm

Akshay Wankhede
Application Engineer
AutoForm Engineering USA
Mr. Wankhede is actively engaged with AutoForm clients, utilizing AutoForm simulation software to develop stamping dies to specific requirements, supporting customer questions and resolving issues in the areas of die construction, hot forming, hydroforming and springback. Mr. Wankhede holds a Bachelor’s degree from Nagpur University in Mechanical Engineering and a Master’s Degree from the University of Missouri-Columbia in Mechanical Engineering.


A Look at the New EU Legislation for Cars and Vans

A Look at the New EU Legislation for Cars and Vans

We’ve been monitoring the evolution of vehicle legislation in the world closely, advocating for life cycle thinking to be considered for the next generation of regulations. The European Union has been actively pursuing Post 2020 regulations, looking hard at CO2 emissions reduction. On 15 May, the new EU CO2 emission legislation for cars and vans for the post-2021 period entered into force, with the objective of contributing to decarbonisation and modernisation of Europe’s road transport sector in line with the EU’s commitments under the Paris International Climate Agreement. The main instrument to achieve this is a further reduction of tailpipe CO2 emissions from new cars by 37.5% by 2030 compared with the 2021 baseline as well as providing incentives to car manufacturers to sell more low-emission vehicles (<50gCO2/km) in the EU.

The direction of EU policy appears clear: cars need to emit less CO2. Others are questioning the focus on emissions reduction in the use phase of a vehicle and whether this will result in overall emissions savings. In fact, improvements in the driving phase could be cancelled out by increased emissions from the production and later the recycling of the vehicle as manufacturers turn to alternative materials and powertrains that could be more energy intensive to produce.

So, what is the solution?

Perhaps it is already in the recently adopted EU. The legislative text is for all intents and purposes a continuation of the existing CO2 emission legislation with more stringent tailpipe-based targets and verification. Yet it features one notable new element: the idea of reporting on the life cycle emissions of cars.

Article 7 – Monitoring and reporting of average emissions
10. The Commission shall no later than 2023 evaluate the possibility of developing a common Union methodology for the assessment and the consistent data reporting of the full life-cycle CO2 emissions of passenger cars and light commercial vehicles that are placed on the Union market. The Commission shall transmit to the European Parliament and to the Council that evaluation, including, where appropriate, proposals for follow-up measures, such as legislative proposals.

By 2023, the European Commission is tasked with assessing the feasibility of creating an EU methodology for harmonised and consistent reporting of full vehicle life cycle CO2 emissions.

Figure 1: Average historical CO2 emission values and adopted CO2 standards for new passenger cars in the EU. All CO2 values refer to New European Driving Cycle (NEDC) measurements. Source: ICCT

With a reporting framework of this kind, regulators could better anticipate the impact of changes in the vehicle fleet on overall emissions and identify the appropriate policy instruments, thereby being able to future-proof the legislation.

Going forward, the European Commission is expected to undertake a feasibility study to identify possible ways to measure vehicle life cycle emissions in a consistent and harmonised way. The conclusions of this work and any possible recommendations for implementing the methodology into EU law would be part of a report to the European Parliament in time for a review of the Regulation by 2023.

As life cycle assessments are already used by a wide range of stakeholders in the automotive sector, it will also be up to them to contribute to this work and help ensure future debates on the best way to decarbonise the EU road transport sector can draw on their experience.


Blanking, Shearing and Trim Operations

Blanking, Shearing and Trim Operations

Advanced Hight-Strength Steels (AHSS) exhibit high work hardening rates, resulting in improved forming capabilities compared to conventional HSLA. However, the same high work hardening creates higher strength and hardness in sheared or punched edges, creating susceptibility to localized strain conditions. In addition, laser cutting samples will also lead to highly localized strength and hardness increases in the cut edge. In general, AHSS can be more sensitive to edge condition because of their higher strength. Therefore, it is important to obtain a good quality edge during the cutting operation. With a good edge, both sheared and laser cut processes can be used to provide adequate formability.

To avoid unexpected problems during a program launch, production intent tooling should be used as early in the development as possible. For example, switching to a sheared edge from a laser-cut edge may lead to problems if the lower ductility, usually associated with a sheared edge, is not accounted for during development.

Trim Blade Design & Blanking Clearances

Cut, sheared, punched or trimmed sheet metal edges have reduced stretchability due to localized work hardening. This work hardened zone can extend one-half metal thickness from the cut edge, therefore, the allowable edge stretchability is less than that predicted by the various forming limit curves. The DP and TRIP steels have islands of martensite located throughout the ferritic microstructure, including the shear zones. These hard particles act as crack initiators and further reduce the allowable edge stretch. These problems are minimized by using laser, EDM or water jet cutting devices that minimize the work hardening and loss of n-value.

Steel company research centers are conducting studies to improve the cutting process by modifying the cutting tool. One program 1 evaluated the design of the punch. Instead of the traditional flat bottom punch, a bevelled design was used. Their conclusion stated the optimized bevel angle was between 3 and 6 degrees, the shear direction was parallel to the rolling direction of the coil and a bevel clearance of 17% was used. With these parameters, the maximum shearing force was significantly reduced, and the hole expansion ratio increased by 60% when compared to a conventional flat punching process.

Figure 1: Cross section of a punched hole of DP780 showing the four main zones of a typical sheared edge.2

Multiple studies have examined the trimmed edge quality based on various cutting conditions. These conditions included different clearances, shear angles, and rake angles on mechanical shearing operations, as well as clearances on slitting operations. Laser cut, water jet and milled edges were also examined. A typical mechanically sheared steel edge has four main zones – rollover, burnish, fracture and burr (see Figure 1). Laser cutting, water jet cutting, EDM and milling are a different story as cold working is not the issue with these processes.

Conventional mild and HSLA steels have historically used burr height as the main measure of edge quality. The typical practice was to maintain burr height below 10% of metal thickness as burrs are stress risers that can lead to edge splitting. As an example, Figure 2 following shows the burr in a BH210 steel blank in the window cut-out area; the subsequent image shows edge splitting in the draw die in this localized area.

Figure 2: Excessive burr on blank (top) and a global formability split on the formed liftgate (bottom) due to excessive work hardening. Dull trim steels were the cause of this condition. 3

Figure 3: Ideal sheared edge with a distinct burnish zone and a smooth fracture zone.

Due to their progressively higher yield and tensile strengths, AHSS grades experience less rollover and smaller burrs (Refer to our previous blog on burr heights). They tend to fracture with very little rollover or burr. As such, detailed examination of the actual edge condition under various cutting conditions becomes more significant with AHSS as opposed to measuring burr height alone to determine edge quality. Multiple studies have found that local formability edge fractures for AHSS are less likely to occur when there is a clearly defined burnish zone with a uniform transition to the fracture zone. The fracture zone should also be smooth with no voids, secondary shear or edge damage (see Figure 3 for photos of an optimal edge condition). If clearances are too small, secondary shear can occur and the potential for voids due to the multiphase microstructure increases (see Figure 4 for edge with secondary shear due to small trim steel clearance).

Clearances that are too large create additional problems that include excessive burrs and voids. A non-uniform transition from the burnish zone to the fracture zone is also undesirable. These non-ideal conditions create propagation sites for edge fractures. HET results and 2D tension test results show a strong correlation between edge condition, HER and percent elongation results. Microstructural analysis of blanked edges, trimmed edges and slit edges should be conducted on a routine basis to assess the edge condition, particularly after die sharpening, tooling modifications, die repair and set-up.

Figure 4: Sheared edge with the trim steel clearance too small (This edge shows secondary shear due to the tight clearance and increases the probability for edge fractures.

There are multiple causes for a poor sheared edge condition. They include die clearances that are too large or too small, a cutting angle that is too small, worn, chipped, or damaged tooling, improperly ground or sharpened tooling, improper die material, improperly heat treated die material, improper (or no) coating on the tooling, misaligned die sections, worn wear plates and out-of-level presses or slitting equipment. The higher loads required to shear AHSS also creates additional deflection of dies and processing equipment. Clearances measured under a static condition may change once the die, press or slitting equipment is put under load due to this deflection. As a large percentage of presses, levellers, straighteners, blankers and slitting equipment were designed years ago, the significantly higher loads required to process today’s AHSS may exceed equipment design limits and alter their performance.

1 Hua-Chu Shih, Constantin Chirac, and Ming Shi, “The Effects of AHSS Shear Edge Conditions on Edge Fracture,” Proceedings of the 2010 International Conference on Manufacturing Science and Engineering, MSEC2010-34062

2 Courtesy of P. Mooney, 3S – Superior Stamping Solutions, LLC

3 P. Mooney, “Stamping Technology Seminar” – 3S – Superior Stamping Solutions, LLC training seminar

Future Mobility – From Moving Cars to Moving People

Future Mobility – From Moving Cars to Moving People

Here at WorldAutoSteel, we have been studying the changes in the automotive industry for several years, focusing particularly on ride sharing, autonomous, electric vehicles and steel’s role in that marketplace.  George Coates, Technical Director for WorldAutoSteel and The Phoenix Group, has been leading that effort and today contributes an article on the disruption of future mobility to the industry and the great opportunities we see for steel in meeting the challenges providers will face.  We hope you enjoy the read, and we welcome your thoughts and comments. What changes and impacts do you envision for vehicle manufacture?  How do you feel about the world of autonomy?

Renault’s Future Mobility concept, the E-Z Go

Renault’s Future Mobility concept, the E-Z Go

We’re approaching a critical milestone in automotive history when what we know as normal is about to change significantly. Future Mobility describes the revolution that’s already begun. We’re rethinking transportation from the movement of a vehicle to a more efficient concept for moving people and things. We’re about to discover the social advantages of connected, autonomous, shared and electric vehicles. And we’re completely changing the way we view transportation.

By 2030, electric vehicles (EVs) will be mainstream—not just within the premium segment, as they are today. EV’s will be popular and available across all vehicle variants and prolific in the commercial vehicle industry and in public transportation. Owners and fleet providers will experience the lower costs of electricity, lower maintenance costs, and the lower overall total cost of ownership (TCO). Fully autonomous or self-driving vehicles will introduce design freedom never experienced before, with the removal of the steering wheel, foot pedals and conventional dashboard. Communication and comfort will be re-imagined, with a vehicle that’s no longer designed around the driver but designed to serve the needs and comfort of the occupants, who are now users instead of owners.

With the rise of mobility services such as Uber, Didi, and a host of others, vehicle ownership is fast becoming an option. In a very short time, especially in urban areas such as China’s mega-cities, it is becoming cost-efficient to subscribe to a monthly ride share service for all of your transportation needs.

Bill Russo, CEO, Automobility LTD

Bill Russo, CEO, Automobility LTD

Bill Russo, CEO of China-based Automobility, in a December 2018 article, Competing in the Digital Internet of Mobility, notes that the digital connectivity of these vehicles will open up profit opportunities well beyond the vehicle hardware. He says “An expanded understanding of mobility use cases and tailoring of the mobility hardware ‘form factor’ to the particular mobility need will be a way to create a value proposition that is rooted in the unique riding experience. In the user-centric world where users are passengers, the focus shifts from traditional driver-centric design to a user-centric productivity space. Instead of traveling in the cockpit, we will move in business class or economy class, depending on our preferences and budget.” Cities will be re-imagined in new social opportunities associated with autonomy, as these vehicles will serve the under-served, and infrastructures will shift in purpose to move people, as opposed to moving vehicles.

Where does steel fit?

The steel industry plans to be right in the middle of this revolutionary change. Fleet owners who provide ride hailing and ride sharing services need to manage the total cost of ownership, while maximizing the user experience for added revenue. To be profitable, they’ll want durable, lasting structures that are affordable to own, provide the user motion as well as emotional comfort, while being efficient to operate, and environmentally friendly – and steel is the only material that meets all these requirements.

On Camera Now: George Coates, Technical Director, WorldAutoSteel and Phoenix Group from worldautosteel on Vimeo.

As always, steel is needed for the crash safety structures, and now add battery protection. Our market intelligence shows that due to the high cost to municipalities and regional governments, autonomous-only vehicles will be limited to dedicated areas for a long time to come. Meanwhile, vehicle-to-vehicle and vehicle-to-infrastructure connectivity will result in dramatic improvements in accident avoidance and reduced fatalities.

Because it will take many years before all vehicles on the road have these technologies in play, the need for passive safety will remain for the foreseeable future. Developing a structural design for the passenger compartment becomes challenging, since there’s a now a need to strike a balance between occupant safety and the occupant freedom. This is enabled by removing the driver and controls from the interior. Steel will be needed to provide the unique properties of both crash energy absorption and deflection, while also managing the loads associated with passengers in multiple and diverse seating configurations. Steel has the ability to provide needed strength while keeping the material thin, which lends more room in the passenger cabin for new seating arrangements and more seats. And battery housings made from steel will provide structural integrity for crash management, while also preventing battery pack damage and leakage.

Lightweighting will continue to be important in an effort to balance smaller battery sizes with maximum range. The steel industry has been and will continue to develop products, such as the ever-growing family of Advanced High-Strength Steels (AHSS), to meet both the mass reduction and the safety targets, affordably. With content innovation and the amazing flexibility of the Iron (Fe) element, researchers still have vast development possibilities for new steels that are stronger, more formable and cost effective.

George Coates is the Technical Director, WorldAutoSteel as well as The Phoenix Group.  Since 1991, George has been providing engineering and consulting services for industry leaders in the steel, automotive, and manufacturing industries. George’s areas of expertise include: management and strategic consulting, project management, automotive stamping throughput improvement, supplier metal conversion, metal formability and reference panel systems, and new vehicle launch manufacturing support. George is an active contributor to WorldAutoSteel technical programs, including project manager / instructor for AHSS Application Guidelines.  George earned a B.S. in Metallurgical Engineering, University of Cincinnati, and his MBA at Miami University (Ohio).
The Value of Mass Benchmarking

The Value of Mass Benchmarking

Product benchmarking is the process of measuring and analyzing the performance of competitive products. Data from a benchmarking analysis is used at the early stages of product development where performance targets are being set for a new vehicle.  As an example of benchmarking, consider setting the mass target for the body structure of a new vehicle program. We want to set a target that is light weight, but also one that is possible to achieve. We benchmark two competitive body structures to help us set the target, Figure 1.

Figure 1: Mass data for two benchmarked vehicles.

From this limited data, it appears a sufficient target for the new program would be 300 kg, the lighter of the two. But there are questions to be resolved: Are these two structures representative of efficient light weighting? Also, if the vehicle under design is of a slightly different size than these two vehicles, how will this affect the applicability of benchmark comparison?

A means to begin to address these concerns is simply to look at more benchmark vehicles. The tear-down database at A2Mac1 Automotive Benchmarking contains mass data for several hundred vehicles. From this database, structure mass for 280 steel sedans is plotted in Figure 2. This expanded data allows us to see a more complete picture of the range of mass exhibited in the market place. Vehicle A and B considered before no longer stand out as exceptional. While this additional data provides an understanding of the average and range of body structure mass, there are concerns with interpreting this chart. Do the lighter structures represent efficient designs or are they just the structures of smaller vehicles?

Figure 2: Body structure mass data for 280 benchmarked vehicles.

We can answer this question by investigating how structure mass varies with mass drivers. Two mass drivers for body structure are vehicle size as measured by plan view area, and structural loading taken to depend on the Gross Vehicle Mass. In Figure 3 we use the same vehicles shown in Figure 2, but now plot structure mass versus each mass driver.

Figure 3: Structure mass vs. vehicle plan view area (left), and gross vehicle mass (right).

The correlation of structure mass for each of these mass drivers is very clearly demonstrated by the trend lines shown: Body structures are heavier for larger cars (left graph), and heavier when they must support greater vehicle mass (right graph). We can quantify these correlations with an equation determined by statistical regression, Equation 1. This equation represents the mass of an average or typical body structure, given its GVM and Area.

Equation 1

mSTRUCT=Mass of body structure (kg)
GVM =Gross vehicle mass (kg)
Area =Plan view area (Length x Width) (m2)

Now for each of the vehicles in our original data set we can calculate the expected structure mass using the vehicle’s GVM and Area. Figure 4 plots the actual measured structure mass vs. the mass expected for that vehicle using Equation 1. The diagonal line indicates those vehicles where the body mass is average or typical. For those structures above the line, body mass is heavier than expected given the area and GVM of the vehicle. And for those below the line, body mass is lighter than expected. This group below the line are the mass efficient body structures that are of interest for fuller analysis.

Figure 4: Actual measured structure mass compared to that expected using equation 1.


Note that looking only at structure mass, as in Figure 2, does not lead to understanding which structures are efficient. For example, Vehicle A in Figure 1 is the lighter of the two structures, 300 kg vs. 325 kg. However, after accounting for the two vehicle’s area and GVM, it can be seen from Figure 4 that Vehicle A is above the diagonal line, indicating a heavier than expected structure, while Vehicle B is on the line indicating it has a typical structure mass.

As a further example, consider the WorldAutoSteel FutureSteelVehicle (FSV). The FSV project, completed in 2011, investigated the weight reduction potential enabled with the use of Advanced High-Strength Steels (AHSS), advanced manufacturing processes, and the use of computer optimization. The resulting material use and body structure mass are shown in Figure 5.

Figure 5: FSV material application and resulting body structure mass.

We can now graph the actual FSV structure mass with expected mass, Figure 6. The data point is well below the diagonal line quantifying the exceptional mass reduction enabled through extensive AHSS use.

Figure 6: FSV body structure compared with 280 normalized benchmarked structures.

Finally, statistical benchmarking reveals which current products would benefit most from lightweighting. Looking again at the plot of actual vs. expected body structure mass for a fixed expected mass, in this case 300 kg, Figure 7. For this set of similarly sized vehicles, there is a wide range of variability in actual mass, indicated by the arrow. For the several vehicles above the diagonal, these body structures are heavier than expected and have significant potential for lightweighting.

Figure 7: Variability in structure mass for similar size vehicles.


For more information on the statistical benchmarking method, see the studies referenced in No. 2 and 3 below. Dr. Malen’s statistical benchmarking methodology also is documented in SAE Paper No. 2015-01-0574

1., Automotive benchmarking.
2. Malen, D., Nagaraj, B., Automotive Mass Benchmarking 2017 study
3. Hughes, J. & Malen, D., Statistical Benchmarking of Automotive Closures, Great Designs in Steel, 2015,
4. FutureSteelVehicle Overview Report, April 2011,

Dr. Donald E. Malen University of Michigan

Dr. Donald E. Malen is an adjunct faculty member at the University of Michigan where he teaches graduate level courses in Automobile Body Structure and Product Design. Prior to this, he was an engineer with General Motors Corporation for 35 years. His background at GM was in automotive body structure design and analysis, and systems engineering. While at GM, he worked on many new vehicle programs and has brought this experience to his teaching and writing. Dr. Malen consults and conducts international seminars on Body Engineering, Innovation, Lead Time Reduction, and Decision Making During Preliminary Design. He holds several patents related to automobile body structure and vibration. His education includes a Ph.D. in Mechanical and Industrial Engineering from the University of Michigan, an MS from Massachusetts Institute of Technology, and a BSME from General Motors Institute (Kettering University).