Bump Steer and Brake Steer Optimization in Steering Linkages Through TAGUCHI Method DOE Analysis 2021-26-0079
Due to recent infrastructural development and emerging competitive automotive markets, there is seen a huge shift in customer’s demand and vehicle drivability pattern in commercial vehicle industry. Now apart from ensuring better vehicle durability and best in class tyre life and fuel mileage, a vehicle manufacturer also has to focus on other key attributes like driver’s safety and ride comfort. Thus, for ensuring enhanced drivability, key parameters for ensuring better vehicle handling includes optimization of bump steer and brake steer. Both bump steer and brake steer are vehicle’s undesirable phenomenon where a driver is forced to constantly make steering wheel correction in order to safely maneuver the vehicle in the desired path. Since both bump steer and brake steer are caused due to the interactions of several vehicle parameters such as - drop arm and steering arm hard point, suspension stiffness, suspension eye and shackle position, caster angle, draglink length etc. their optimization is a complex activity and involves lot of time and design iterations.
Through this paper, a unique approach has been shown for the optimization of bump steer and brake steer contributing factors through Taguchi DOE analysis. Taguchi DOE analysis approach ensures minimum design iterations of various contributing factors and their interactions through standard Taguchi orthogonal arrays. Thus, this method eliminates random trial and error approach and rather demonstrates a structured way of problem solving through limited design iterations. The paper also shows the difference between Taguchi and full factorial DOE analysis and the difference in number of design iterations involved among them. Thus, a complex problem of vehicle’s parameter optimization for ensuring minimum bump steer and brake steer is shown to be resolved through limited design iterations which not only saves overall project time and budget but also provides the user a better insight of the interaction of each variable on vehicle performance which is later evaluated during vehicle physical trials.