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Four-bar linkages are critical fundamental elements of many mechanical systems, and their design synthesis is often mathematically complicated with iterative numerical solutions. Analytical methods based on Fourier coefficients can circumvent these difficulties but have issues with time parameters assignment for path generation without prescribed time in previous studies. In this paper, an improved Fourier-based point-to-point combination method is presented, which generates more points by Fourier approximation and assigns the time parameters to the given points while allowing discarding solutions with order defects. This method relies on the Fourier coefficients, improving the accuracy of synthesis solutions, and simplifying the computational procedure. Time parameters are assigned directly to the given points, which avoids the complex calculations to find intersection points in the given path, eliminates combinations that would lead to solutions with order defects, and simplifies the assessment process of synthesis results. The parameters obtained by the point-to-point combination method can be used as the parameters of the input dyad, skipping the first set of design equations for faster calculation. Several examples are presented to demonstrate the advantages of the proposed synthesis method, which is easy-understanding, computationally efficient, and yields more accurate solutions than available synthesis methods. [ABSTRACT FROM AUTHOR]

Purpose: Auxetics metamaterials show high performance in their specific characteristics, while the absolute stiffness and strength are much weaker due to substantial porosity. This paper aims to propose a novel auxetic honeycomb structure manufactured using selective laser melting and study the enhanced mechanical performance when subjected to in-plane compression loading. Design/methodology/approach: A novel composite structure was designed and fabricated on the basis of an arrowhead auxetic honeycomb and filled with polyurethane foam. The deformation mechanism and mechanical responses of the structure with different structural parameters were investigated experimentally and numerically. With the verified simulation models, the effects of parameters on compression strength and energy absorption characteristics were further discussed through parametric analysis. Findings: A good agreement was achieved between the experimental and simulation results, showing an evidently enhanced compression strength and energy absorption capacity. The interaction between the auxetic honeycomb and foam reveals to exploit a reinforcement effect on the compression performance. The parametric analysis indicates that the composite with smaller included angel and higher foam density exhibits higher plateau stress and better specific energy absorption, while increasing strut thickness is undesirable for high energy absorption efficiency. Originality/value: The results of this study served to demonstrate an enhanced mechanical performance for the foam filled auxetic honeycomb, which is expected to be exploited with applications in aerospace, automobile, civil engineering and protective devices. The findings of this study can provide numerical and experimental references for the design of structural parameters. [ABSTRACT FROM AUTHOR]

In this paper, a fault diagnosis method based on CPSO-BP neural network is proposed for civil aircraft cabindoor retracting system to address such issues as high simulation cost, limited fault data, and low fault diagnosis accuracy. Considering the operating characteristics and frequent faults of the civil aircraft cabindoor system, four typical failures, namely, flow control valve wear, hydraulic motor leakage, hydraulic oil pollution and throttle valve blockage, are identified. Based on AMESim, an aircraft cabindoor system simulation model is built, 120 sets of fault data are obtained by simulation analysis of the typical faults, and a fault data set containing 29 520 samples is built. A fault diagnosis by BP neural network reveals the average accuracy rate of fault diagnosis only stands at 85. 36%. In comparison, the chaotic particle swarm optimization algorithm (CPSO), which optimizes both the initial weight and threshold of BP neural network, increases the accuracy rate to 93%, demonstrating better fault diagnosis performance. [ABSTRACT FROM AUTHOR]

In the current research, the main method to improve passenger safety in collision accidents and achieve lightweight of body-in-white (BIW) is deterministic optimization. Due to the perturbations of the design variables, the deterministic optimization results will be invalid. To solve this problem, a multi-objective reliability method based on integrating surrogate model and Six-Sigma criteria is proposed. As an example, a finite element model of a light-duty vehicle has been developed and validated by full-scale crash test. Through analyzing the overall energy absorption performance during frontal crash simulation, six main parts have screened, and their thickness values have been selected as design variables. Increasing energy absorption and reducing the weight of the structure were selected as design objectives. The front wall invasion (D), the peak acceleration (A) and the energy difference ΙΔEΙ absorbed by the left and right side stringer are as constrains. Take the design variables obey normal distribution, and use a genetic algorithm method to generate Pareto solutions. The Pareto solutions of different iteration numbers with a sigma level of 4.5 are analyzed, and the results show that both deterministic optimization and reliability optimization can increase energy absorption. While deterministic optimization increases total energy absorption by 7.6%, but the total weight is increased by 6.9%. And the reliability of the two constraint functions front wall invasion and peak acceleration are lower than 60%. The reliability optimization decreases the weight by 5.3% and increases the energy absorption by 11.7%. Meanwhile, the value of constraint functions are lower, which is beneficial to the crashworthiness of the vehicle, and the reliability of them reaches more than 99%. [ABSTRACT FROM AUTHOR]

In congested street or highway scenarios, such as lane-change in dynamically changing traffic flow situations, the planning and tracking of trajectories for connected and automated vehicles (CAVs) represent some of the most challenging tasks. As an introduction to automated lane-change in CAVs, this paper presents a control Lyapunov function (CLF) approach that follows an optimal desired trajectory while observing the constraints imposed by the control barrier function (CBF) in order to avoid collision with surrounding vehicles. By combining CLF and CBF within the framework of quadratic programs (QP), it allows the implementation to simultaneously track the control objective (represented by the CLF) and satisfy the constraints of the desired state of the system (represented by the CBF). Therefore, it provides the possibility of tracking simultaneously the path of the unmanned vehicle, within the constraints of the surrounding vehicles as well as the surrounding environment. From simulations and comparison results, the controller presented here can perform collision avoidance well and can be used on a real traffic system, which has the advantage of providing faster and more precise lane-change results than another work. [ABSTRACT FROM AUTHOR]

Two-dimensional materials have been developed as novel photovoltaic and photocatalytic devices because of their excellent properties. In this work, four δ-IV–VI monolayers, GeS, GeSe, SiS and SiSe, are investigated as semiconductors with desirable bandgaps using the first-principles method. These δ-IV–VI monolayers exhibit exceptional toughness; in particular, the yield strength of the GeSe monolayer has no obvious deterioration at 30% strain. Interestingly, the GeSe monolayer also possesses ultrahigh electron mobility along the x direction of approximately 32,507 cm2·V−1·s−1, which is much higher than that of the other δ-IV–VI monolayers. Moreover, the calculated capacity for hydrogen evolution reaction of these δ-IV–VI monolayers further implies their potential for applications in photovoltaic and nano-devices. [ABSTRACT FROM AUTHOR]

The flow field in the original duct was simulated using Reynolds-average Navier–Stokes methods. Grid independence test was carried out and the air velocity at four outlets was consistent with experimental data, so the accuracy of the numerical model can be guaranteed. Vortex at the inner wall of the curved duct was identified from the simulation result, and two 75° guide plates with the thickness of 1 mm were used to reduce it. The vortex was well improved and the flow path of air became more regular than the original scheme. Guide plates with gradual increasing height along the airflow direction at the straight duct were proposed to improve the uniformity. The height of the last guide plate was set to 50 mm, the same as original scheme; then, the smallest standard deviation of velocity at four outlets is achieved with the increasing ratio of 1.4. [ABSTRACT FROM AUTHOR]

Eco-cruising is considered an effective approach for reducing energy consumption of connected vehicles. Most eco-cruising controllers (ECs) do not comply with real-time implementation requirements when a short sampling interval is required. This paper presents a solution to this problem. Model predictive control (MPC) framework was applied to the speed-planning problem for a power-split hybrid electric vehicle (HEV). To overcome the limitations of time-domain MPC (TMPC), a nonlinear space-domain MPC (SMPC) was proposed in the space domain. A real-time iteration (RTI) algorithm was developed to accelerate nonlinear SMPC computations via generating warm initializations and subsequently forming the SMPC-RTI. Proposed speed controllers were evaluated in a hierarchical EC, where a heuristic energy management strategy was selected for powertrain control. Simulation results indicated that the proposed SMPC yields comparable fuel savings to the TMPC and the globally optimal solution. Meanwhile, SMPC reduced MPC computation time by 41% compared to TMPC, and SMPC-RTI further reduced MPC computation time without compromising optimization. During the hardware-in-loop (HIL) test, the mean computation time was 9.86 ms, demonstrating potential for real-time applications. [ABSTRACT FROM AUTHOR]

Thin‐walled structures are used extensively in the passive safety of vehicles to absorb energy. The thin‐walled tube is already a traditional structure with excellent energy absorption. Negative Poisson's ratio (NPR) structures produce an inward concentration to increase the stiffness of the structure during axial compression. The concept of fluctuation of crushing force (FoCF) is introduced herein to evaluate this new energy‐absorbing box as an energy‐absorbing device based on the traditional energy absorption evaluation index. Based on experimental validation, a finite‐element model is developed that can accurately predict the crashworthiness of the double‐V NPR‐filled square tube (DVFST). The following parameters, such as out‐of‐plane thickness, meta‐cell half‐width beam thickness, and beam angle tube thickness, are conducted to assess the crashworthiness of the DVFST structure. The first thing that should be considered in the design of the DVFST structure is the half‐width of the cell, followed by the angle of the long beam, and then the relative wall thickness of the long and short beams. The DVFST structure has the potential to become an excellent energy‐absorbing device by adjusting its parameters. [ABSTRACT FROM AUTHOR]

This paper presents two nonlinear model predictive control (MPC) methods for the integrated propulsion and cabin-cooling management of electric vehicles. An air-conditioning (AC) model, which has previously been validated on a real system, is used to accomplish system-level optimization. To investigate the optimal solution for the integrated optimal control problem (OCP), we first build an MPC, referred to as a joint MPC, in which the goal is to minimize battery energy consumption while maintaining cabin-cooling comfort. Second, we divide the integrated OCP into two small-scale problems and devise a co-optimization MPC (co-MPC), where speed planning on hilly roads and cabin-cooling management with propulsion power information are addressed successively. Our proposed MPC methods are then validated through two case studies. The results show that both the joint MPC and co-MPC can produce significant energy benefits while maintaining driving and thermal comfort. Compared to regular constant-speed cruise control that is equipped with a proportion integral (PI)-based AC controller, the benefits to the battery energy earned by the joint MPC and co-MPC range from 2.09% to 2.72%. Furthermore, compared with the joint MPC, the co-MPC method can achieve comparable performance in energy consumption and temperature regulation but with reduced computation time. [ABSTRACT FROM AUTHOR]

In order to improve the motion accuracy and robustness of the clutch mechanical leg for driving robot (CMLDR), and to improve the shift performance of the driving robot vehicle (DRV) for the engagement operation of CMLDR, a neural network adaptive robust control method of shift process for CMLDR with clutch transmission torque compensation is proposed. First, the dynamics model of the driving robot is established considering an external interference force and dynamic modeling error of the mechanical leg. Second, the upper clutch controller including a two-parameter shift module, a switch controller, and a finite-time linear quadratic regulator of the clutch transmission torque is designed. Third, the estimator of clutch engagement torque through a Kalman filter in the process of shift is constructed. Then, the neural network adaptive robust (NNAR) controller of the mechanical leg is designed. Finally, the proof of stability analysis for NNAR controller is conducted. Experiment and simulation results show that the designed controller of the mechanical leg has a strong antiinterference ability. And the DRV accurately tracks the target speed after compensating for the transmission torque. [ABSTRACT FROM AUTHOR]

Bioinspired structure/material has attracted attentions in engineering fields. In this article, a novel sandwich cylinder inspired by shore horsetail is proposed by introducing the double-arrowed auxetic filler. The energy absorption characteristics of the sandwich cylinder are analysed comprehensively and compared to the conventional structure to show its superiority. The effects of the geometric parameters on the energy absorption characteristics are also discussed. It is found that the number of layers and cells for auxetic structures, thickness of beams and thin-walled tubes, and the radius of the inner tube have great effects on the crushing force, energy absorption, initial peak force and specific energy absorption. The sandwich cylinder will be a great energy absorber after designing. [ABSTRACT FROM AUTHOR]

With the widespread use of robots in the world, including rescue operations and special surgeries, the precise design of robots is of particular importance. The shift manipulator is a part of the robot driver structure which is composed of a two-degree of freedom parallel mechanism with electric cylinders. The singularity analysis and inertia torque analysis are conducted based on the kinematic and dynamic models. The integrated design variables for multi-objective optimization are proposed to evaluate the kinematic and dynamic performance of the manipulator. Given dimensional parameters as design variables and geometric constraints in a moving area, the multi-objective integrated optimization model is established and solved by the Simulated Annealing Particle Swarm Algorithm (SA-PSA). Furthermore, the optimized performance is compared with different optimal methods, and the effectiveness of the presented method using SA-PSA is verified by performance simulations and test. The results demonstrate that the kinematic and dynamic performances are improved 22.22% through minimizing two integrated design variables. [ABSTRACT FROM AUTHOR]

One challenge of bearing fault diagnosis is that the vibration signals are often a nonlinear mixture of unknown source signals. In addition, the practical installation position also limits the number of observed signals. Hence, bearing fault diagnosis is a nonlinear underdetermined blind source separation (UBSS) problem. In this paper, a novel nonlinear UBSS solution based on source number estimation and improved sparse component analysis (SCA) is proposed. Firstly, the ensemble empirical mode decomposition (EEMD), correlation coefficient (CC), and adaptive threshold singular value decomposition (ATSVD) joint approach is proposed to estimate the source number. Then, the observed signals are transformed into the time−frequency domain by short−time Fourier transform (STFT) to meet the sparsity requirement of SCA. The frequency energy is adopted to increase the accuracy of fuzzy C−means (FCM) clustering, so as to ensure the accuracy estimation of the mixing matrix. The L1−norm minimization is utilized to recover the source signals. Simulation results prove that the proposed UBSS solution can exactly estimate the source number and effectively separate the simulated signals in both linear and nonlinear mixed cases. Finally, bearing fault testbed experiments are conducted to verify the validity of the proposed approach in bearing fault diagnosis. [ABSTRACT FROM AUTHOR]

Ecological cruising control methods of vehicles have been extensively studied to further cut down energy consumption by optimizing vehicles' speed profiles. However, most controllers cannot be put into practical application because of future terrain data requirements and excessive computational demand. In this paper, an eco-cruising strategy with real-time capability utilizing deep reinforcement learning is proposed for electric vehicles (EVs) propelled by in-wheel motors. The deep deterministic policy gradient algorithm is leveraged to continuously regulate the motor torque in response to road elevation changes. By comparing the proposed strategy to the energy economy benchmark optimized with dynamic programming (DP), and traditional constant speed (CS) strategy, its learning ability, optimality, and generalization performance are verified. The simulation results show that without a priori knowledge about the future trip, the proposed strategy provides 3.8% energy saving compared with the CS strategy. It also yields a smaller gap than the globally optimal solution of DP. By testing on other driving cycles, the trained strategy reveals good generalization performance and impressive computational efficiency (about 2 ms per simulation step), making it practical and implementable. Additionally, the model-free characteristic of the proposed strategy makes it applicable for EVs with different powertrain topologies. [ABSTRACT FROM AUTHOR]

At present, most straight bevel gears use a root fillet transition surface with a radius of 0.3 modulus. This tends to cause excessive root bending stress and reduces the service life of bevel gears. In order to solve this problem, a root fillet transition surface controlled by a set of third-order Bezier curves is designed based on spherical involute tooth surface. In the common cone apex coordinate system of the bevel gear, the spherical involute tooth surface equations and the third-order Bezier curve equations controlling the root transition surface are established. The feasibility of gear manufacturing is verified by precision forging simulation. A Box–Behnken experiment was designed, and the response surface model was developed from the experimental results. The response surface model reflects the mathematical relationship between the four variables controlling the third-order Bezier curve and the maximum tooth root bending stress. Then, the nonlinear programming was used to optimize the four variables, and the optimal root transition surface was obtained. [ABSTRACT FROM AUTHOR]

A novel structure with enhanced energy absorption is proposed by introducing thin-walled tube as the inner liner tube of the cylindrical structures with negative Poisson's ratio (C-NPR). The energy absorption performances of C-NPR structure with inner tube (C-NPR-IT) are compared to other configurations like the single NPR structure, single thin-walled tube, and C-NPR structure with outer tube (C-NPR-OT) to show its superiority. It is found that the interaction between the NPR structure and inner tube in C-NPR-IT can be enhanced. Then, the parametric analysis of the geometric parameters on the crashworthiness performance of C-NPR-IT structures are performed with finite element method. To achieve the best configuration, the surrogate modeling technique and the multi-objective particle swarm optimization (MOPSO) algorithm are employed to optimize the C-NPR-IT structures. The results show that the optimized structure improves the specific energy absorption (SEA) from 3.97 to 10.26 kJ/kg by almost 2.5× by controlling peak crushing force (PCF) less than 80 kN. Therefore, the C-NPR-IT structure has an application prospective in the energy absorber. [ABSTRACT FROM AUTHOR]

Fault diagnosis of gearboxes based on vibration signal processing is challenging, as vibration signals collected by acceleration sensors are typically a nonlinear mixture of unknown signals. Furthermore, the number of source signals is usually larger than that of sensors because of the practical limitation on sensor positions. Hence, the fault characterization is actually a nonlinear underdetermined blind source separation (NUBSS) problem. In this paper, a novel NUBSS algorithm based on kernel independent component analysis (KICA) and antlion optimization (ALO) is proposed to address the technical challenge. The mathematical model demonstrates the nonlinear mixing of source signals in the underdetermined cases. Ensemble empirical mode decomposition is used as a preprocessing tool to decompose the observed signals into a set of intrinsic mode functions that suffers from the problem of redundant components. The correlation coefficient is utilized to eliminate the redundant components. An adaptive threshold singular value decomposition method is proposed to estimate the number of source signals. Then a whitening process is carried out to transform the overdetermined blind source separation (BSS) into determined BSS, which can be solved by the KICA method. However, the reasonable selection of parameters in KICA limits its application to some extent. Therefore, ALO and Fisher's linear discriminant analysis are adopted to further enhance the accuracy of the KICA method. The separation performance of the proposed method is assessed through simulation. The numerical results show that the proposed method can accurately estimate the number of source signals and attains a higher separation quality in tackling nonlinear mixed signals when compared with the existing methods. Finally, the inner ring fault experiment is conducted to preliminarily validate the practicability of the proposed method in bearing fault diagnosis. [ABSTRACT FROM AUTHOR]

This paper proposes an integrated lane-change trajectory planning method for advanced driver assistance system of connected and automated vehicles. First, the time-based quintic polynomial automated lane-change model is presented, which could adjust longitudinal and lateral velocity simultaneously. By tuning the lane-change duration and longitudinal displacement in the lane-change model, the lane-change reference trajectories satisfying the demands of safety, lane-change duration, travel distance, and comfort were derived under traffic-free condition. All feasible reference trajectories compose a trajectory map, which includes different driving situations, such as quick and comfortable or sudden and safe lane change. Second, the lane-change constraints induced by surrounding vehicles are introduced. The effects of surrounding vehicles on the lane-change performance are investigated by adjusting the speeds and initial gaps of preceding and rear vehicles. In addition, the initial velocity of the host vehicle is optimized to maximize the area of the trajectory map to enable a safer lane change. Finally, within the derived trajectory map, an optimal lane-change trajectory eliminating potential collisions is calculated by minimizing the lane-change duration, travel distance, driving comfort, and fuel consumption. [ABSTRACT FROM AUTHOR]

Crash-box is a significant part of automotive passive safety system and serves as a main energy absorption device in frontal impact scenario. In this paper, a novel crash-box integrating an outer thin-walled tube and an inner auxetic cellular core has been designed and comprehensively investigated under axial load. The impact simulation of the auxetic crash-box has been carried out, and the results show that introduction of the auxetic core can improve its energy absorption capacity without increasing too much peak impact force. Based on the sensitivity analysis, the effects of its geometric parameters on the crashworthiness performance have been studied. Finally, collaborative optimization of the auxetic crash-box has been performed to simultaneously improve its crashworthiness under the low-speed (15 km/h) and high-speed (40 km/h) impact cases. In the optimization procedure, the least square support vector regression (LS-SVR) method and an improved particle swarm optimization (IPSO) algorithm with time-varying coefficients have been utilized. The results demonstrate that the optimized crash-box can comprehensively improve the energy absorption and impact force characteristics effectively. The auxetic crash-box and the collaborative optimization approach provide extensive references for the application of auxetic structure in vehicle crashworthiness design. [ABSTRACT FROM AUTHOR]

Power-split hybrid technologies have been transformed from single mode to multimode to realize even greater savings in fuel and more powerful output. However, the optimization procedure of the mode shift map for multimode hybrid electric vehicles (HEVs) has not been formalized. In this paper, the types of mode shift are first classified as direct/indirect and conditional/unconditional. The optimal shift path with minimum energy variation for the indirect mode shift is formulated as a shortest path problem and solved by Dijkstra’s algorithm. By taking the energy loss during mode shift into consideration, the method for designing a mode shift map is presented from the perspective of the normalized system efficiency. The derived mode shift map is combined with a novel energy management strategy, referred to as normalized efficiency maximum strategy, to formulate an integrated real-time control strategy for the multimode HEV. Finally, by comparing two other commonly used strategies, dynamic programing and equivalent consumption minimization strategy, the proposed control strategy shows great potential in improving fuel economy while maintaining smooth engine operation, thus leading to better ride comfort of the vehicle. [ABSTRACT FROM AUTHOR]

Periodic cellular structures, especially lattice designs, have potential to improve the cooling performance of brake disk system. In this paper, the method of two scales asymptotic homogenization was used to indicate the effective elastic stiffnesses of lattice plates structures. The arbitrary topology of lattice core cells connected to the back and front plates which are made of generally orthotropic materials, due to use in brake disc design. This starts with the derivation of general shell model with consideration of the set of unit cell problems and then making use of the model to determine the analytical equations and calculate the effective elastic properties of lattice plate concerning the connected back and front plates. The analytical and numerical method allows determining the stiffness properties and the internal forces in the trusses and plates of the lattice. Three types of core-based lattice plates, which are pyramidal, X-type and I-type lattices, have been studied. The I-type lattice is characterized here for the first time with particular attention on the role that the cell trusses and plates plays on the stiffness and strength properties. The lattice designs are finite element characterized and compared with the numerical and experimentally validated pyramidal and X-type lattices under identical conditions. The I-type lattice provides 4% higher strength more than the other lattice types with 9% higher truss fraction coefficient. Results show that the stiffness and yield strength of the lattices depend upon the stress–strain response of the parent alloy of trusses and plates, the truss mass fraction coefficient, the face carriers thickness and the core elements parameters. The study described here is limited to a linear analysis of lattice properties. Geometric nonlinearities, however, have a considerable impact on the effective behavior of a lattice and will be the subject of future studies. [ABSTRACT FROM AUTHOR]

Structures with negative Poisson's ratio (NPR) have been widely used in engineering application due to its unusual properties. In this paper, crashworthiness of a novel cylindrical auxetic structure under axial impact loading is investigated by the numerical methods. The software LS-DYNA is adopted to analyze the effects of the geometry parameters on the force, energy absorption (EA) and specific energy absorption (SEA). It is found that an overlarge number of layers and cells will make NPR structure extend outward from the mid; NPR structures with small number of layers and cells will make some layers of structures rotate in final crushing state. If the thickness of the long-inclined bean (L-beam) is larger than that of short-inclined beam (S-beam), there will be a smoother transition from the lower to a higher value in crushing force. Conversely, the force will maintain a relatively steady value, which determined by the sum of the thickness of L- and S-beams. In addition, there is also a critical inner circle radius which distinguishes different deformation modes. Once the critical inner circle radius is smaller than the critical value, NPR structures tend to deform unsteadily. [ABSTRACT FROM AUTHOR]

Improving the energy efficiency of an electric vehicle (EV) is an effective approach to extend its driving range. This paper proposes an integrated energy-oriented lateral stability controller (IESC) for a four-wheel independent-drive EV (4WID-EV) to optimize its energy consumption while maintaining vehicular stability during cornering. The IESC is a hierarchical controller with two levels. The high-level decision-making controller determines the virtual control inputs, i.e., the desired additional yaw moment and total wheel torque, while the low-level controller allocates the motor torques according to the virtual control inputs. In the high-level controller, the desired additional yaw moment is first calculated using a linear quadratic regulator (LQR) to minimize the control expenditure. Meanwhile, a stability weighting factor (SWF) based on phase plane analysis is proposed to adjust the additional yaw moment, which can reduce the additional energy consumption caused by the mismatch between the reference model and the actual vehicle. In addition to the yaw moment, the desired total wheel torque is calculated using a proportional-integral (PI) controller to track the desired longitudinal velocity. In the low-level controller, a multi-objective convex-optimization problem is established to optimize the motor torque by minimizing the energy consumption and considering the tire-road frictional limit and motor saturation. A globally optimal solution is obtained by using an active-set method. Finally, double-lane change (DLC) simulations are conducted using CarSim and MATLAB/Simulink. The simulation results demonstrate that the proposed controller achieves great lateral stability control performance and reduces the energy consumption by 5.23% and 2.95% compared with the rule-based control strategy for high- and low-friction DLC maneuvers, respectively. [ABSTRACT FROM AUTHOR]

The in-plane uniaxial and biaxial crushing characteristics of three honeycombs were studied through explicit dynamic finite element analysis in this paper. Crushing models were created, with all square specimens (hexagonal, reentrant and mixed honeycombs) deliberately built in the same scale. The in-plane uniaxial compressive performances of cellular structures in terms of the deformation mode, plateau stress, energy absorption as well as the impact response were compared and discussed, respectively. In the same loading condition, these honeycombs exhibited distinct characteristics. After that, in-plane orthogonal biaxial crushing simulations were carried out. Deformation processes of honeycombs were analyzed and compared. Results illustrated that some deformation behaviors in the uniaxial crushing case still exist in the biaxial crushing analysis. Their deformation modes were drawn into deformation maps. Energy absorption research illustrated that the transverse shrinking property in the uniaxial crushing case was detrimental to the energy dissipation capacity of honeycomb in the biaxial crushing case. In addition, comparing with the hexagonal honeycomb, reentrant honeycomb with slightly thicker cell walls expressed weaker ability in specific energy dissipation. [ABSTRACT FROM AUTHOR]

Tolerance analysis of mechanical components and assemblies is a key element in the industry for improving product quality and reducing overall cost. This paper is an attempt to propose a methodology to formulate and compute the kinematic assembly variations with respect to the critical dimensions (joint clearances) by calculating the homogeneous matrix of loops with considering the transforming and rotation matrix, the tolerance sensitivities, the geometrical responses to assembly variations, and the tolerance sensitivity of mechanism for clearance in the joints in different motion phases. The analysis is performed by the systematic methodology which is extended for kinematic sensitivity and positional error analysis with published results. [ABSTRACT FROM AUTHOR]

Jounce bumpers in automotive suspension are key components that can improve the noise, vibration, and harshness performance of entire vehicle. Traditional jounce bumper made of polyurethane usually cannot satisfy the mechanical performances required by noise, vibration, and harshness optimization. In addition, the application of hyperelastic material influenced the efficiency and reliability of numerical calculations of polyurethane jounce bumper. In this paper, an engineering negative Poisson’s ratio structure was introduced and applied on the jounce bumper. The negative Poisson’s ratio jounce bumper can be mainly defined by few structure parameters. The finite element analysis of the negative Poisson’s ratio jounce bumper was conducted applied explicit method. The influences of loading velocity and material densities on computational time and numerical results were researched. The results indicated that enlargements of material densities and loading velocity can improve the computational efficiency and have limited influence on reliability. Furthermore, a negative Poisson’s ratio jounce bumper prototype was manufactured and tested to verify the numerical results. It was proved that the finite element analysis of the negative Poisson’s ratio jounce bumper was reliable both in load–displacement curve and deformation shapes. Compared to the traditional jounce bumper, the negative Poisson’s ratio jounce bumper can achieve similar mechanical behavior but with a smoother load–displacement curve, which is beneficial to the vehicle’s noise, vibration, and harshness performance. [ABSTRACT FROM AUTHOR]

The design of blast-resistant vehicle provides an appropriate level of protection for the vehicle and occupants against the serious threat from landmine and improvised explosive devices (IED). Mathematically, the objective of this research is to optimize the configuration of light armored vehicle installed multilayer honeycomb sandwich structures (MHSS), shock-mitigating seat and seat belt, and cope with the challenge of highly computational cost on dealing with the large scale, multi-parameter, nonlinear and fluid-structure interaction simulation models. Multi material Arbitrary Lagrangian-Eulerian (MM-ALE) method is used to obtain the high-precision vehicle responses and occupant injuries under blast wave. The baseline model validated by the blast test is built, and the optimization model for blast-resistant vehicle is defined. Then, identifying important design parameters accurately is so difficultly when sufficient samples are not provided due to the expensive computational cost, and it's inappropriate to screen parameters with inconsistent sequence of variable sensitivities for occupant injuries. Factor analysis based multi-parameter optimization (FAMO) is proposed to reduce the computational cost on improving the blast resistant performance of vehicle. The normal-boundary intersection (NBI) and the R metric are used to obtain optimal compromise solution which noticeable reduced the peak value of occupant injuries, and the physical insights which drive the optimal solution to reduce the occupant injuries is analyzed. Additional studies are conducted on comparing between proposed algorithm and the conventional algorithm, including shape of the Pareto front, optimal compromise solution, design variables and responses. [ABSTRACT FROM AUTHOR]

In this paper, fatigue damage analysis and structural improvement of a commercial vehicle cab were carried out, in which a simulation technique and durability road tests were combined. A full-scale finite element model of the cab was established and then validated by means of physical testing and analysis of its stiffness and its modal performance. The loading spectra, in accordance with the durability road test, were obtained by adopting the virtual iteration method. With the established finite element model, the stress distributions in the cab under unit excitation were determined. The obtained stress distributions were then used to assess the total fatigue life of the cab by employing the strain–life (ε–N) method; thus, the critical regions were determined. The results showed that some components near the pillars and mounts are easy to damage because of the stress concentrations. It was also demonstrated that the predicted regions are reliable, which was verified by comparison with the physical durability road tests. Finally, structural improvements in the critical structures were made; the fatigue life assessment of the improved cab showed an obvious improvement in its durability performance. [ABSTRACT FROM AUTHOR]

Hybrid powertrain technologies must be applied to sports utility vehicles (SUV) and light trucks (LT) in the near future to meet the new corporate average fuel economy standards. For SUV and LT, multimode hybrid powertrains using multiple planetary gears (PGs) help to deliver the required torque while achieving better fuel economy. Compared with single and double PG systems, three-PG system can provide more design flexibility. However, it is not practical to search through all possible three-PG designs using exhaustive search methods because of the enormous size of the design space. In this paper, a rapid structure optimization method is proposed. Fuel-saving (FS) modes and high launching performance (HLP) modes are first identified through normalized efficiency analysis and maximum output torque analysis. Then, a constrained optimization problem is defined to limit the mode candidates (FS and HLP modes). Following this approach, the design space is reduced by a factor of 1000. Three clutch designs are obtained from the designs with fewer clutches (one or two) by using the design-extension technique. Finally, a case study demonstrates how the proposed method is applied to the optimal design of three-PG hybrids. [ABSTRACT FROM PUBLISHER]

The primary problem in the finite element analysis of polyurethane jounce bumpers, bumper stops, or similar structures is the identification of a mathematical model for the constitutive material. The densities of the exterior polyurethane area and the interior polyurethane area usually differ owing to the manufacturing process. This difference results in inaccuracy when predicting the mechanical behavior of the jounce bumper and bumper stop if a homogeneous material model is used. Thus, this work proposes a stratification method for finite element analysis of a polyurethane jounce bumper. The polyurethane structure was divided into three regions (the ‘skin layer’, the ‘transition layer’, and the ‘core area’) with different material properties. A foam model was utilized as the constitutive relationship. The foam model coefficients of the core area were obtained by a curve-fitting process using uniaxial compression test results. Subsequently, the material properties of the skin layer and the transition layer were also obtained. The finite element analysis results show that the proposed stratification strategy improves the prediction of the deformed shapes of the polyurethane jounce bumper. Furthermore, the calculated load–displacement curve is reliable for small to medium strains (0–0.4). Therefore, the proposed stratification method can be applied to enhance the reliability of jounce bumper simulations and to simplify the design process. [ABSTRACT FROM AUTHOR]

Because of limitations in the vehicle layout, a central brake system was installed directly on the transmission’s back case of a certain type of medium-size truck. Under the condition of emergency braking, the back case easily fails because of the large braking torque. In this paper, a method of structure improvement, finite element analysis and experimental investigations of the transmission’s back case was proposed. Two improved designs of the back case are discussed. The finite element analysis results indicated that the improved back case was capable of bearing the maximum braking torque, which was also verified by vehicle road tests and torque tests. The modal analysis results implied that the lowest free modal frequency of the improved back case was increased and far away from the engine excitation frequency. In addition, the first-order constrained modal frequency was also greater than the gear meshing frequency. The overall results implied that the improved design of the transmission’s back case was applicable under normal conditions, and the proposed method was sufficiently accurate for wide use. [ABSTRACT FROM AUTHOR]

This paper proposes a multirate processing technique for obtaining integer and fractional derivatives of digital signals with an improved signal-to-quantization noise ratio. The technique consists of an oversampling analog-to-digital conversion unit with a dithering process and multistage down sampling process followed by an half-band finite impulse response (FIR) differentiator with high performance cascaded using a decimator with a factor of two. In the cascaded multistage processing, each stage contains a simple half-band low-pass FIR filter followed with decimation by two. The proposed technique uses an extremely small size for each half-band low-pass filter, hence requiring much less memory and computational complexity in comparison with the single-stage process. Computer simulations and experimental data processing demonstrate the effectiveness of the proposed method. [ABSTRACT FROM PUBLISHER]

In this paper, a new IIR notch filter with transient suppression is proposed. The proposed algorithm utilizes a varying pole radius to significantly reduce the transient effect when eliminating a sinusoidal interference in signal enhancement. Based on a time-varying linear difference equation, the analytical solution to a sinusoidal interference is found. With a given tolerance of the transient disturbance, a scheme is derived to predict the duration of the transient response and to determine the damping parameter used for changing the pole radius. Computer simulations demonstrate that the developed pole-radius-varying IIR notch filter significantly outperforms the traditional IIR notch filter. [ABSTRACT FROM AUTHOR]

In this paper, a framework for obtaining the higher order derivative of digital signals with an improved signal-to-quantization-noise ratio (SQNR) is developed. The framework consists of an oversampling analog-to-digital conversion unit with a dithering process and a higher order finite-impulse response (FIR) digital differentiator followed by a decimator. A simple and effective recursion is derived for designing the higher order FIR digital differentiator. In addition, the SQNR is analyzed. Computer simulations validate the proposed framework, the differentiator design method, and the results of the improved SQNR. [ABSTRACT FROM AUTHOR]

Dynamic behaviors of the three-dimensional re-entrant auxetic cellular structure have been investigated by performing beam-based crushing simulation. Detailed deformation process subjected to various crushing velocities has been described, where three specific crushing modes have been identified with respect to the crushing velocity and the relative density. The crushing strength of the 3D re-entrant auxetic structure reveals to increase with increasing crushing velocity and relative density. Moreover, an analytical formula of dynamic plateau stress has been deduced, which has been validated to present theoretical predictions agreeing well with simulation results. By establishing an analytical model, the role of relative density on the energy absorption capacity of the 3D re-entrant auxetic structure has been further studied. The results indicate that the specific plastic energy dissipation is increased by increasing the relative density, while the normalized plastic energy dissipation has an opposite sensitivity to the relative density when the crushing velocity exceeds the critical transition velocity. The study in this work can provide insights into the dynamic property of the 3D re-entrant auxetic structure and provides an extensive reference for the crushing resistance design of the auxetic structure. [ABSTRACT FROM AUTHOR]