This paper was produced for the 2019 NAFEMS World Congress in Quebec Canada
Electrically powered steering column drive (EPS-CD) is a technology used to provide assist torque, as well as new steering features, for A to D segment vehicles. The main advantages of that technology is to support CO₂ reduction, fuel economy and automated driving.
This product is divided mainly in two assemblies:
1 . Steering column assembly responsible for comfort adjustment features, static and dynamic loading requirements, as well as passive safety requirements.
2. Power unit assembly consisting in an electrical motor, engine control unit, software and gearbox responsible to create the assist and new steering functions
The following paper is focused in the passive safety requirement for an EPS-CD product.
The steering column products is one of the main elements of the passive safety restraint system in a passenger vehicle. The columns are designed to collapse in a frontal crash event generating an optimized ride down force to reduce chest and head injuries of the driver. This is a driver requirement when developing a new steering column design.
The steering column crash response is normally generated by several elements and interfaces, where many of them have also requirements in other functionalities in addition to passive safety. That results in a complex validation scenario of fusible and deformable elements, friction force contributors, all of them made of different materials (plastics, greased steel, casted aluminium components).
That multiple sources of variability is reducing the confidence in classic finite elements approach where normally the nominal and few best worst case conditions are considered for analysis, as well as from the real hardware testing side where that variability generates extra effort at the end of projects with a huge impact in the project costs and time (when few number of prototype parts are available). It is known that reality, especially when we are talking in the manufacturing field, there is a huge variability, and in that scenario the pass-fail criteria changes from a target value to a range of performance. This has been the main motivation when defining the scope of the project, “to bring manufacturing variability in the design process”.
As part of ZF lean validation strategy a new method has been developed to improve the system robustness in ZF Active safety division by means of virtual simulation and six sigma disciplines. The results obtained applying this new method are also applicable for a model based development process and democratization.
In a nutshell the method starts with an analysis of variance of crash system response using a correlated virtual model, where the main parameters affecting the crash response are known (normally applicable after any new core development process). As a result of the analysis, it is obtained the regression equations of the system response.
As a second step, a Monte Carlo simulation had been applied using the equation obtained generating statistical results for a number of cases (based in the design tolerances) not manageable from the hardware testing perspective, neither from the finite elements methods. In that project, the Monte Carlo simulation has been applied for 100 000 load cases generating probabilistic response instead of “deterministic response” (one geometry, one result).
With these two steps we have been able to create the manufacturing variability response for a destructive test in a highly cost and time effective approach.
In addition, these equations have three more benefits equally or even more beneficial:
1. The equations define and quantify the importance of each factor, and consequently they can be used to generate a validation plan from component to system and enables to generate adequate component requirements as per a Model Based Development procedure
2. Democratization, the regression equation can be forwarded to designing team (or PLM tool), giving them an analytical tool for quick verification of main crash contributors.
3. Building customer confidence, as part of the democratization, the equation can be used during the requirement elicitation phase with customers generating confidence in the acceptance criteria.