Browse Topic: Brake components
The automotive industry's transition towards electrification, particularly in the passenger car (PC) and light commercial vehicle (LCV) segments, has intensified the focus on vehicle lightweighting to maximize battery range and efficiency. Conventional brake systems in electric vehicles (EVs) are subject to minimal mechanical wear due to regenerative braking, making corrosion the primary cause of component failure and replacement. This paper details the development and production of an innovative lightweight brake, which addresses these challenges. The "Cast-In" brake disc combines a traditional gray cast iron friction ring with a pre-finished, deep-drawn steel hat through a specialized composite casting process. This design achieves a significant reduction in unsprung mass—1.6 kg per disc in a 390mm x 36mm example—directly contributing to improved vehicle dynamics and energy efficiency. Key manufacturing challenges, including ensuring a robust material bond, preventing casting defects, and sealing the steel hat during casting, have been overcome through advanced process controls, simulation, and a patented sealing system. Furthermore, a novel, enhanced corrosion protection system has been developed and validated to meet the required service life of over 10 years, addressing the specific demands of e-mobility. With production scheduled to begin in April 2026, this technology is a milestone for modern braking solutions in the era of electrification.
Moan noise is a low-frequency noise occurring in the 170–500 Hz frequency ranges. While it frequently appears in vehicles equipped with a rear Coupled Torsion Beam Axle (CTBA), the exact cause, generation mechanism and clear solutions remain unidentified. For those reasons, we have developed a moan noise analysis method capable of representing the moan noise phenomenon in vehicles with rear CTBA along with an automation tool. From these results, we can use moan analysis models to reduce real moan noise problems. Consequently, this not only enhances customer satisfaction and vehicle quality but also significantly increases the work efficiency of vehicle designers through design modification in the preliminary stages of vehicle development
Commercial vehicle fleets frequently operate with tractors that connect to different trailers and dollies, resulting in combinations with varying brake pad wear across wheel ends. Traditional brake-force distribution strategies do not consider these pad-life differences, which can lead to uneven brake utilization, irregular maintenance intervals, and increased total cost of ownership (TCO) in mixed-trailer operations [7, 9]. While modern electronically controlled braking systems (EBS) already incorporate pad wear based braking for the tractor itself [5], these capabilities do not extend across the entire vehicle combination because trailer-side communication is typically limited to standardized CAN protocols such as ISO 11992 and J1939 [1, 2, 3]. As braking systems become more software defined and rely heavily on distributed electronic communication, ensuring the authenticity and integrity of trailer originated brake information becomes essential for both functional safety and cybersecurity [6]. In the proposed architecture, trailers and dollies communicate brake related data to the tractor over the ISO 11992 Tractor-Trailer CAN (TT-CAN) network [1, 2], allowing the tractor Brake Control ECU to securely validate the source of the information and register each towed unit for health aware braking. Once authenticated pad life data is available, the tractor constructs a combination level brake health map covering every wheel end in the configuration. During normal braking, a supervisory allocator computes wheel end specific brake pressure targets that bias braking toward wheel ends with greater remaining pad life while ensuring full compliance with stopping distance regulations and stability requirements [4, 7]. By integrating authenticated pad wear information with tractor hosted supervisory control, the system improves braking consistency across mixed combinations, harmonizes pad utilization, enhances maintenance predictability, and reduces TCO while meeting the safety and cybersecurity expectations of modern commercial vehicle fleets.
Drum brake systems are becoming increasingly important in electric vehicles (EV) and purpose-built vehicles due to cost competitiveness and EURO-7 particulate emission regulations. Despite this trend, drum brake friction behavior remains incompletely characterized due to its dependence on multiple coupled variables: temperature history, braking conditions, and component interactions. To address this gap, this study presents a method for developing a time-series friction torque prediction model using the Mixed-effects Random Forest (MERF) machine learning framework. Time-series data collected from sensors during drum brake dynamometer tests were analyzed to identify the key variables that govern the friction torque. Significant inputs were selected through Exploratory Data Analysis (EDA), considering test-to-test variability and potential mixed effects, and were then used to train and tune the MERF model. Model performance was evaluated by comparing predicted friction torque with measured torque, and prediction error was quantified by using Mean Absolute Error (MAE) to check whether predicted model is reliable. The proposed prediction model demonstrates a high level of agreement with experimental measurements, confirming that the MERF approach can effectively capture the non-linear and transient characteristics of drum brake friction torque from time-series sensor signals. These results indicate that friction torque estimation is feasible using only sensor signals already available from conventional test instrumentation, without additional dedicated sensors. This capability is expected to support broader applications, including brake performance prediction for vehicles equipped with drum brakes and enhanced simulation of drum brake thermal performance across operating conditions.
It was reported earlier that the wear differential between the inboard pad and the outboard pad leads to brake squeal generation. The (inboard/outboard) pads wear differential can occur due to hardware issues such as brake pad drag and/or two different wear rates of the (I/O) pads, which is caused by two different material properties of the pads although the pad formula may be the same. It is found that (I/O) pads compressibility differential/hardness differential/friction differential are all interrelated and that they contribute to brake squeal generation in addition to the inboard pad tangential/radial taper wear. A method has been found to separate the inboard pad friction and the outboard pad friction and to estimate each friction coefficient.
A unified thermomechanical fatigue (TMF) life-prediction methodology is presented for lamellar graphite (grey) cast iron brake rotors operating under the severe transient thermal loads that arise in brake dynamometer durability testing. The workflow links four ingredients within a single rotor-level framework: transient nonlinear finite-element analysis, temperature-dependent inelastic constitutive modeling, a mechanism-based short-crack TMF damage model, and an elastic-plastic (nonlinear) fracture-mechanics crack-growth simulation. Two constitutive descriptions are exercised for the structural analysis — the standard rate-dependent Chaboche viscoplastic model available in Abaqus, and a user material subroutine (UMAT) that couples Chaboche viscoplasticity with continuum damage in order to reproduce the tension–compression asymmetry of cast iron. The resulting stress, strain, and temperature histories drive a multiaxial thermomechanical fatigue Damage (DTMF) computation that estimates crack initiation and early extension, after which a nonlinear fracture-mechanics procedure simulates crack-front advance toward through-thickness failure. Both constitutive models correctly localize the crack-initiation site on the rotor inner diameter, consistent with the dynamometer observations; for the loading histories examined, the standard Chaboche model yields lives in closer agreement with test. The crack-growth simulation reproduces the rapid post-initiation propagation seen experimentally and resolves branch-wise differences in crack-front evolution through the rotor section.
The increasing pressure to decarbonize manufacturing systems is pushing industry beyond conventional lightweighting strategies toward material and process paradigms, capable of delivering functional performance with radically lower environmental impact. In this context, polymer-based composite Additive Manufacturing (AM) offers an underexplored yet highly promising pathway for sustainable production of load-bearing components. This study presents a preliminary comparative cradle-to-gate Life Cycle Assessment (LCA) of a Formula SAE brake pedal, assessing the environmental transition from conventional sheet metal fabrication and finishing operations of Aluminum 7075-T6 to additive manufacturing solutions, with specific focus on Carbon-Fiber-Reinforced Polymer (CFRP) composites. Two topology-optimized designs, respectively for Powder Bed Fusion (PBF) in AlSi10Mg and Material Extrusion (MEX) in Polyethylene Terephthalate Glycol with Carbon Fiber (PETG-CF) are compared to conventional fabrication aluminum benchmark. The analysis is integrated in the product and process design following ISO 14040/14044 standards and is implemented using the Environmental Footprint 3.0 methodology within the 3DEXPERIENCE platform. Results outline that Material Extrusion (MEX) composite manufacturing achieves the lowest environmental impact across all evaluated categories. Compared to conventional manufacturing, the PETG-CF solution enables an approximate 50% reduction in Global Warming Potential and an almost complete elimination of mineral depletion. Unlike metal additive manufacturing, which remains constrained by high process energy demand, MEX benefits from low processing temperatures, minimal auxiliary systems, and highly efficient material deposition. Crucially, these sustainability gains are achieved while maintaining functional performance through design-driven topology optimization. AM composite solutions, by merging advanced material science with additive flexibility, may lead to design approaches which cease to be ‘potential’ enablers of sustainable manufacturing for the Industry 5.0 transition.
As the adoption of electric vehicles continues to accelerate, the demand for their development and testing using chassis dynamometers has also increased significantly. Compared with internal combustion engine vehicles, chassis dynamometer testing for electric vehicles typically requires test durations several to several dozen times longer, resulting in substantially increased labor requirements. In addition, low-temperature testing is often required, further intensifying the workload associated with vehicle testing. To address these challenges, this study developed and evaluated a pedal robot designed to enable unmanned and automated testing. The pedal robot developed in this study weighs only 12 kg and can be installed within a few minutes. It is, to the authors’ knowledge, the world’s first pedal robot that mimics human driving behavior by using a single foot to operate both the accelerator and brake pedals. Unlike conventional driving robots, the actuators of the proposed system do not require direct mechanical attachment to the vehicle pedals, allowing for rapid installation. Furthermore, the robot is mounted on the driver-side floor, eliminating the need for attachment to the seat structure. The pedal robot features three degrees of freedom driven by three motors and employs artificial intelligence to recognize the shape and position of pedals across different vehicle models, thereby enabling automated test initiation without manual adjustment. The performance of the pedal robot was evaluated under UDDS, HWFET, and WLTC driving modes, and the results were analyzed in accordance with the SAE J2951 standard. Comparative evaluations demonstrated that the pedal robot achieved superior speed-tracking performance relative to that of an experienced human test driver. The developed pedal robot is currently being utilized for vehicle certification testing of electric and other vehicles at the Mobile Environment Research Center of the National Institute of Environmental Research in Korea. This paper presents a detailed analysis of the corresponding experimental results.
The objective of this paper is to evaluate the thermal performance of the brake discs in the design stage of its life cycle by developing a methodology to replicate dynamometer testing using multi-disciplinary Finite Element Analysis (FEA) methods. A simulation workflow was formulated in which Computational Fluid Dynamics (CFD) was used to create temperature and velocity dependent Heat Transfer Coefficients (HTC) which were in turn used in Computer Aided Engineering (CAE) to do a thermo-mechanical analysis. With this workflow various designs of the brake discs were analyzed. A sensitivity study was done to determine critical design features that affected its thermal performance. A final design was fixed that met both the weight and thermal performance targets. This design was evaluated in dynamometer testing, and 93% correlation was achieved. Thus, the developed simulation workflow ensured that a first-time right brake disc can be finalized in the design stage, which will meet the performance in dynamometer testing.
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