Browse Topic: Traction
Tire noise reduction is important for improving ride comfort, especially in electric vehicle due to lack of engine noise and majority of the noise generated in-cabin is from tire-road interaction. Therefore, the tire tread pattern contribution is one of the important criteria for NVH performance apart from other structurally generated noise and vibration. In this work a GUI-based pitch sequence optimization tool is developed to support tire design engineers in generating acoustically optimized tread sequences. The tool operates in two modes: without constraints, where the pitch sequence is optimized freely to reduce tonal noise levels; and with constraints, where specific design rules are applied to preserve pattern consistency and manufacturability. The key point to be considered in this pitch sequence is that it should be reducing the tonal sound and equally spread i.e., the same pitch cannot be concentrated on one side which may lead to non-uniformity. So, the restriction is that
The problem of monitoring the parametric failures of a traction electric drive unit consisting of an inverter, a traction machine and a gearbox when interacting with a battery management system has been solved. The strategy for solving the problem is considered for an electric drive with three-phase synchronous and induction machines. The drive power elements perform electromechanical energy conversion with additional losses. The losses are caused by deviations of the element parameters from the nominal values during operation. Monitoring gradual failures by additional losses is adopted as a key concept of on-board diagnostics. Deviation monitoring places increased demands on the information support and accuracy of mathematical models of power elements. We take into account that the first harmonics of currents and voltages of a three-phase circuit are the dominant energy source, higher harmonics of PWM appear as harmonic losses, and mechanical losses in the rotor and gearbox can be
Vehicle handling is significantly influenced by aerodynamic forces, which alter the normal load distribution across all four wheels, affecting vehicle stability. These forces, including lift, drag, and side forces, cause complex weight transfers and vary non-linearly with vehicle apparent velocity and orientation relative to wind direction. In this study, we simulate the vehicle traveling on a circular path with constant steering input, calculate the normal load on each tire using a weight transfer formula, calculate the effect of lift force on the vehicle on the front and rear, and calculate the vehicle dynamic relation at steady state because the frequency of change due to aerodynamic load is significantly less than that of the yaw rate response. The wind velocity vector is constant while the vehicle drives in a circle, so the apparent wind velocity relative to the car is cyclical. Our approach focuses on the interaction between two fundamental non-linearity’s: the nonlinear
The sideslip angle and tire-road peak adhesion coefficient (TRPAC) are crucial parameters for intelligent active safety systems in automobiles. The accuracy and real-time estimation of these parameters significantly affect control effectiveness. And there is a strong coupling between the two parameters, which brings great challenges to the joint estimation. This paper proposes a nonlinear dynamic estimator that pre-estimates tire lateral force to achieve synchronous estimation of sideslip angle and TRPAC. Additionally, to cope with sudden changes in road adhesion condition, a TRPAC preliminary estimation optimization algorithm is introduced. Moreover, an adaptive gain adjustment algorithm for the sideslip angle estimator is implemented to address large lateral excitation conditions. Simulation results on various road surfaces and under various lateral excitation conditions demonstrate that the proposed joint estimator enables accurate and rapid estimation of sideslip angle and TRPAC.
General Motors (GM) is working towards a future world of zero crashes, zero emissions and zero congestion. It’s “Ultium” platform has revolutionized electric vehicle drive units to provide versatile yet thrilling driving experience to the customers. Three variants of traction power inverter modules (TPIMs) including a dual channel inverter configuration are designed in collaboration with LG Magna e-Powertrain (LGM). These TPIMs are integrated with other power electronics components inside Integrated power electronics (IPE) to eliminate redundant high voltage connections and increase power density. The developed power module from LGM has used state-of-the art sintering technology and double-sided cooled structure to achieve industry leading performance and reliability. All the components are engineered with high level of integration skills to utilize across TPIM variants. Each component in the design is rigorously analyzed and tested from component to system levels to ensure high
Symbolic code execution is a powerful cybersecurity testing approach that facilitates the systematic exploration of all paths within a program to uncover previously unknown cybersecurity vulnerabilities. This is achieved through a Satisfiability Modulo Theory (SMT) solver, which operates on symbolic values for program inputs instead of using their concrete counterparts. However, in complex code bases, this approach faces significant limitations, such as program path explosions or unavailable dependencies, which can result in conditions that the SMT solver cannot reason about. Consequently, SMT solvers are often considered as too costly to implement for automotive testing use cases and are rarely employed within this domain. In contrast, fuzz testing has recently gained traction in the automotive industry as an invaluable testing technique for identifying previously unknown vulnerabilities. Its initial setup is straightforward and typically yields useful findings. However, achieving
In the quest for sustainable materials for automotive interior trim, jute fiber is gaining traction due to its characteristics, which align with other renowned natural fibers. This study aimed to assess the efficacy of sodium bicarbonate as a treatment for jute fibers in comparison to conventional alkaline treatments. Both treated and untreated fibers were examined. Results showed that alkali-processed fibers demonstrated enhanced crystallization, thermal resistance, and surface quality relative to untreated ones. Specifically, alkali-treated jute fibers exhibited a degradation onset at 261.23°C, while those treated with sodium bicarbonate began degrading at 246.32°C. Untreated fibers had a degradation onset at 239.25°C. Although both treatments improved the thermal stability of the fiber, sodium bicarbonate processing, while beneficial, was slightly less effective than the traditional alkaline method. Overall, the research underscores the potential of sodium bicarbonate as an
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