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 highest and lowest pitch types cannot occur adjacent to one another. This design rule helps in reducing undesirable pattern non-uniformity and improves both acoustic and structural performance. This tool helps in faster design iteration and integration with downstream development processes. This tool is also validated in current OE projects showing promising improvements in tire noise behavior while maintaining realistic design feasibility.
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 many times greater than electrical losses in high-speed modes of traction machines. The paper pays special attention to monitoring the three-phase circuit of a traction machine by a measuring observer consisting of six current and voltage sensors. Algorithms for data processing using the generalized energy flow technology are presented. They allow obtaining comprehensive information on the energy state of a three-phase circuit with a time delay of no more than one millisecond. The three-phase circuit monitoring data are taken as a basis for monitoring electrical and polarization losses of the battery, electrical and switching losses of the voltage inverter, electrical, magnetic, harmonic and mechanical losses of the motor and gearbox.
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 aerodynamic forces and the nonlinear relationship between tire lateral force, attack angles, and normal loads. Real-time calculation of the understeer coefficient is performed as the vehicle traverses the circular path. We then compared how yaw rate, tire slip angles, and understeer changed for different types of cars (neutral, understeer, and oversteer) at various car and wind speeds. The understeer car showed high variation as at certain speeds the vehicle switched from understeer to slight oversteer due to loss of traction at rear tires.
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.
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 high code coverage with fuzz testing is quite challenging and requires a sophisticated instrumentation and guidance setup. A promising approach to address this challenge of insufficient code coverage involves combining symbolic code execution with substituted values from the fuzzing engine for complex conditions, enabling the SMT solver to handle them effectively. In this paper, we present an overview of the current state of concolic testing tools and their applicability in the automotive domain. We compare concolic testing to conventional fuzz testing setups commonly observed in the automotive industry and outline the conditions necessary to achieve greater code coverage, thereby increasing the likelihood of discovering vulnerabilities.
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 reliability, power density and efficiency. All these topics mentioned above are within the scope of this paper.
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 alternative treatment for fibrous materials, even if its efficacy is somewhat lesser than traditional methods. The findings offer insights into optimizing jute fiber for automotive interior trim applications.
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