A Novel Analytical Approach to Predict Vehicle Parking Brake Cable Performance and Optimize Cable Routing

The performance of vehicle parking brake cables are critical for ensuring vehicle safety and functionality. Vehicle manufacturer evaluate the robustness of cable performance at different road gradient conditions. Effort and stroke performance are among the key parameters for evaluating cable performance. While parking brake system should be designed to minimize effort losses through the cable routing, packaging constraints often prevent it. Therefore, it is essential to estimate the losses through cable routing and optimize parameters of the parking brake cable system. Currently, the methods used for evaluating cable performance are either experimental or empirical based. CAE methods using finite element analysis (FEA) and multibody dynamic approaches are computationally expensive and not yet fully established due to modelling and solving complexity of dynamic cable which involves continuously changing and updating contacts. The available analytical approaches incorporates cable system geometric parameters and material properties, however vehicle level details are not yet fully incorporated. In this study, a novel analytical methodology is developed to evaluate parking brake cable performance, including effort losses and efficiency, as well as stroke losses and efficiency. The proposal incorporates the integration of BiW (Body-in-White) clamp placements and overhang connections, along with the cable. Detailed geometric and material properties of the cable, along with the friction coefficient between the cable and sleeve for both dry and lubricated conditions, are considered. The rope and pulley principle is used to predict effort losses through the cable routing, and the uniform displacement method is used to calculate force distribution among the cables. This method is experimentally validated through rig and vehicle-level tests, and a sensitivity study is performed to evaluate the relative contribution of different parameters. This methodology can further be used for optimization and design finalization. This analytical method reduces CAE-based simulation time and minimizes multiple testing iterations before finalizing designs.