Abstract:Changes in human body parameters influence on the geometry of the ribcage in children, directly affecting the form of chest injury. A limited number of existing children's ribcage geometric models were developed using the parameters of specific body characteristics. CT 3D reconstruction，semi-automatic point selection，ribcage posture adjustment, statistical analysis，and Radial Basis Function（RBF） neural network deformation were applied to 61 CTs，and then a parametric geometric model for children's ribcage aged 3~12 years in China based on the age, height，Body Mass Index（BMI）， and gender was developed. Using the proposed parametric geometric model，the children's ribcage geometry models depending on the age（3~12 years old），height，BMI，and gender can be quickly obtained. The average geometric accuracy of the predicted ribcage geometry model for children aged 3~12 years was 5.2 mm, and the average geometric accuracy of the first to the twelfth pairs of ribs was at most 7.0 mm, and at least 4.5 mm. The parametric geometry model can be used to study the effect of human body parameters on the geometry of children's ribcage and its impact on children's chest injury.

Abstract:The wind-induced vibration of the car rearview mirror blurs the image, which brings great danger to driving safety. The method of two-way FSI（Fluid-Structure Interaction）was applied to the numerical simulation on the vibration problem of rearview mirror caused by airflow around the Driver model. STAR-CCM+ and Abaqus were used for co-simulation. According to the comparison and analysis of the vibration characteristics of fixed rearview mirror as well as the rearview mirror with wind-induced vibration at different flow velocity and under the condition of side wind, the conclusion can be drawn as follows: as it is affected by the vehicle body, the vortex falling from the edge of mirror is difficult to develop in the wake, which limits the vortex-induced vibration. The mirror vibration is dominated by the wind speed, the vibration frequency is maintained at 27.8 Hz，and the higher wind speed results in the larger amplitude. When there is crosswind，force of the flow field on the rearview mirror is disordered, dominant frequency disappears in the low frequency area, and the vibration intensifies. In this situation, the vortex is fully developed in the wake, which induces the strong vibration of about 164.5 Hz.

Abstract:In order to quantify the effects of different seat cushion density on driver/passengers' sitting comfort, a 95th percentile human-body model that meets the Chinese physical structure and a driver/passenger-automotive seat model of different density were built，which simulated the driver/passengers' general body pressure distribution and body-parts' pressure distribution with different foaming density of automotive seats. The simulation results showed that this paper more precisely determined the variation rule of pressure distribution and shear force between seats with different foaming density and occupants, shortened the seats' research period, then quantitatively and delicately analyzed the impact of different seat cushion density on sitting comfort during the concept design stage before commissioning.

Abstract:Aiming at the coupling phenomenon of longitudinal and lateral motions for automobile, autonomous vehicle with Four-wheel-driving and front-wheel-steering was set as the subject investigated. A dynamic model which reflects the longitudinal and lateral motion of vehicle was established and the reversibility of this model was analyzed by the interactor algorithm. On the basis of the existing classical structure of pseudo-linear system, the pseudo linear composition system with the ability to fit the upper level planning system of intelligent vehicle was established according to the characteristic of intelligent vehicle. In order to realize the decoupling of longitudinal and lateral motions for vehicle, an approach based on network inverse method was proposed as the decoupling control strategy in this paper, which can be combined with the internal model controller to form closed loop structure and it can significantly improve the performance of the plant by feedback and adjust the longitudinal speed and yaw rate of automobile. The simulation results validated the decoupling performance of the proposed approach. The results also showed that when compared with other control algorithms, the proposed approach can achieve good tracking performance of longitudinal speed and yaw rate under varieties of input condition. Further, the sideslip was constrained in a small range, which is beneficial to the path tracing accuracy and the stability of autonomous vehicle.

Abstract:Automated driving vehicles have problems in local trajectory planning, such as insufficient consideration of vehicle handling stability, excessive simplification of vehicle models, and lack of objective evaluation of vehicle comfort. Considering the stability of vehicle handling, a three-degree-of-freedom model of vehicle is established. The lane changing scene of the self-driving car is simulated. The lane-changing trajectory is output by inputting the wheel angle，and the parameterization equation and driving trajectory characteristics of the vehicle are calculated. The BP neural network is used to identify the trajectory characteristics, and the change relationship between the lane change duration and lateral offset distance of the autonomous driving vehicle is obtained. At different lane changing speeds, according to different lane changing durations and lateral offset distances, the input wheel angles are used to obtain the lane change optimized by the trajectory clusters and steering stability parameters. Based on the conventional trajectory optimization method that only considers the driving efficiency and safety, the trajectory optimization objective function is constructed, by using the value of the yaw, roll, and lateral acceleration rate of the vehicle lane change process. A comprehensive trajectory optimization method based on driving efficiency, safety, comfort and steering stability is proposed. The trajectory optimization objective function is solved to obtain the optimal lane change trajectory. The joint simulation results show that the method is superior to the conventional trajectory optimization method, and the comfort and steering stability are improved by more than 20%.

Abstract:In order to solve the limitation of the hydrogen consumption as an economic evaluation index for the fuel cell hybrid bus, an equivalent hydrogen consumption model and a multi-objective optimization function combining quality and life factors were adopted, and the economical key parameters relevant to the whole life cycle were optimized in this paper. The total system cost and energy system mass were reduced by the optimization. The simulation results show that the super capacitor can still fully play the role of “shaving the peak and filling the valley”，the battery cannot output or input large current, the cycle equivalent hydrogen consumption and the average current of the battery remains basically unchanged before and after optimization, the output power of the fuel cell is stable, and the fuel cell voltage decay is only reduced by 2 μV. It should be noted that the degree of decay of the lifespan is little. The optimization method proposed can ensure the life and economic efficiency, the equivalent hydrogen consumption of the cycle conditions is basically the same, and the total cost and total mass of the system are optimized to a greater degree, accelerating the application of fuel cell hybrid energy system in bus.

Abstract:Synthetically considering the effects of friction, fit clearance and weight, this study established the theoretical calculation model for the maximum axial bearing capacity of hydraulic cylinders. The influence rule of the frictions at two ends on the axial bearing capacity was studied. It was also simulated by finite element software, which was finally verified by related test data. The results show that the maximum axial bearing capacity calculated by the established theoretical model, compared with the test value, has an error of 13.5%, which indicates that the established theoretical model is reliable. The maximum axial bearing capacity increases with the decrease of the length-to-diameter ratios of piston rod and cylinder, or the increase of friction coefficient. However, excessive friction changes the connection state of the two ends of the hydraulic cylinder, which converts slide state to fixed state and results in abrupt increase of axial bearing capacity. With the decrease of the piston rod and cylinder lengths, or the increase of the piston rod diameter, the impact of friction on the axial bearing capacity increases. However, when the cylinder barrel diameter changes, the impact of friction on the bearing capacity is not changed. This research can provide important reference for the design and performance verification of hydraulic cylinder.

Abstract:At present, the FMEA (Failure Mode and Effect Analysis) for electromechanical products is cumbersome, time-consuming, and error-prone. The analysis objects of this method also cannot reflect the characteristics of “motion determines function” in electromechanical products. In order to address such problems, firstly, according to the decomposition idea of “function-motion-action”，the function of electromechanical products is decomposed into the most basic action (that is, meta-action); secondly, the characteristics of meta-action are analyzed, and the rationality of taking meta-action as the research object of electromechanical products FMEA is discussed; thirdly, based on those above, a M-FMEA (Meta-action Failure Mode and Effect Analysis) method for electromechanical products is proposed; finally, traditional methods and the proposed method are compared in rationality, applicability and simplicity, which highlights the advantages of the proposed method. A numerical control machine tool made in China is taken as an example, the applicability and effectiveness of the proposed method are verified, and the accuracy and efficiency of failure analysis for electromechanical products are also improved.

Abstract:In this paper, a composite curved beam structure used in high stiffness components of space launch platform is designed，and its mechanical properties are studied experimentally and numerically. Firstly, the static loading test of the curved beam is carried out by a computer controlled electronic testing machine. The load-displacement characteristic curves of the curved beam are obtained, and the equivalent elastic modulus is calculated. Based on ABAQUS finite element software, the finite element model of curved beam is established, and the numerical computations under different displacement loads are carried out. The experimental data are used to verify the numerical results. The calculated results are in good agreement with the measured results, and the errors are less than 10%. Then, the finite element model is used to calculate the longitudinal and transverse displacements of curved beams under different loads. It is concluded that the longitudinal displacement of curved beam is small, the transverse displacement is large, and the ratio of transverse displacement to longitudinal displacement is greater than 10. The effects of thickness of curved beam, width of clearance, and length of central straight beam on the mechanical properties of curved beam are studied, and the rules of the influence of different geometric parameters on the equivalent elastic modulus are obtained. This study provides a reference for the application of curved beams in the vibration isolation devices.

Abstract:Signal noise interference, adaptability of battery model to temperature and aging, and inconsistency of the battery pack are vital factors which have the influence on the accuracy of State of Charge（SOC） estimation. To estimate the SOC of battery pack accurately, this paper proposes a novel method that combines the Interacting Multiple Model (IMM) and the Adaptive Battery State Estimator（ABSE）. Firstly, the battery interaction models are established based on the comprehensive characteristics of the battery pack. The SOC is estimated by ABSE and embedded in the IMM model. Then, the information distribution factors of each model are calculated, and the SOC of each model is probabilistically fused according to the information distribution factors to obtain a battery pack SOC with higher precision. Finally, the robustness and universality of the algorithm are evaluated under combined conditions of different temperature. The experimental results show that this method is effective for various conditions including the input signals with noise，complicated condition under the whole climate, and inconsistency between batteries.The estimation error can be controlled within the range of 2% during effective charging and discharging cycles.

Abstract:The power-voltage characteristic curve of photovoltaic system has multiple peaks under partial shade condition. The traditional maximum power tracking method can easily trace to the local maximum power point. To solve such shortcoming，a photovoltaic system Maximum Power Point Tracking（MPPT） algorithm based on adaptive radial basis function neural network is proposed. The model optimizes the extended constants and weights of RBF neural network with adaptive linear algorithm, which overcomes the shortcomings of traditional neural network algorithm with slow convergence speed and poor global optimization. The simulation of adaptive RBF neural network is carried out in MATLAB/Simulink environment. The results show that the proposed algorithm can accurately find the maximum power point of the photovoltaic system when the external illumination and temperature change. Moreover the convergence accuracy and convergence time are greatly improved.

Abstract:Since it is difficult to quickly control the internal energy of the converter, which may cause problems such as unbalanced energy between the arms in the modular multilevel converter based high voltage direct current (MMC-HVDC) system，this paper proposes a control strategy of MMC based on energy balancing control from the internal mechanism of the converter, optimizing the control of the current components of each arm. The control strategy can realize the coordinated control of the AC side current and the internal energy of the converter，and effectively reduce the internal energy unbalanced process caused by the converter during the system fault process. Finally, the MMC simulation model is built on MATLAB/Simulink，and the simulation results verify the effectiveness of the proposed control strategy.

Abstract:Access point assignment for indoor Li-Fi and Radio Frequency (RF) hybrid networks is studied. Based on the dynamic application scenario with the movement of users and the changes in the number of users, a conversion threshold is introduced to determine the allocation of APs. Two improved methods of AP allocations, dynamic threshold and minimum data rate constraint, are proposed under the condition of considering the handover overhead. The experimental results show that in the same application scenario, the proposed AP allocation methods improve the outage probability performance by 4.66% and 8.50%, respectively, and improve 1% outage data rate by 3.21 Mb/s and 9.09 Mb/s, respectively, when compared with the AP allocation method with fixed threshold. In addition, the simulation analysis shows that the data rate requirements and the maximum number of randomly generated users can significantly affect the outage probability performance.

Abstract:Aiming at the problems such as low flexibility, long development cycle, and incapability of adapting to rapidly changing algorithms for current video decoder implementation solutions, a generic video decoder architecture design scheme for multiple video coding and decoding standards is proposed using software and hardware collaboration. The methodology of the design is based on a programmable homogeneous multi-core processor and coprocessor hardware architecture. The homogeneous multi-core processor uses instruction-level and task-level parallel acceleration. The coprocessor uses a hardware customization unit to achieve the vector acceleration, while it uses distributed on-chip scratchpad memory instead of data cache to achieve an efficient data storage system. Taking the H.264 video standard widely used as an example, the experimental results show that the H.264 video decoder based on the architecture proposed in this paper is highly efficient and feasible, with an average speed-up of 9.12, which is 1.31 times better than the traditional multi-core parallel decoding algorithm.

Abstract:In a diffuse optical channel，the visible light indoor positioning is affected by first-order reflection and noise，and thus the positioning error in boundary region is relatively larger than that in interior region. To solve this problem，a positioning algorithm of subregional visible light indoor based on multilayer Extreme Learning Machine (ELM) was proposed in this paper，and the effectiveness of the proposed algorithm was verified by simulation experiments. Firstly，the first layer ELM based on the entire experimental region was established to calculate the entire positioning error. Secondly，the second layer ELM based on the magnitude and distribution characteristics of positioning error was established，and the entire experimental region was divided into boundary subregion and interior subregion. Thirdly，the third layer ELM based on the extracted boundary subregion was established to calculate the boundary positioning error. Lastly，the entire error with updated boundary error was used to realize the positioning. The experimental results show that the entire average positioning error of the proposed algorithm is 2.79 cm. Compared with the Received Signal Strength（RSS） and Back Propagation（BP） neural networks，the average positioning error is reduced by 13 times and 55.36%，respectively. Compared with the single-layer ELM，the boundary average positioning error is reduced by 65.66%，the entire average positioning error is reduced by 23.77%. Experimental results indicate that the boundary positioning error of the proposed algorithm is obviously decreased，which means the proposed algorithm has higher positioning accuracy and robustness，and is suitable for various positioning applications.

Abstract:Single Shot MultiBox Detector (SSD) is generally considered to be suitable for solving small target detection in images. However，its performance on feature extraction and detection efficiency is still required to be improved. A clustering residual SSD model is proposed in this paper. On one hand，in order to improve the feature extraction quality，the basic network VGG16 which consists of the original SSD model is replaced with a deeper residual network ResNet50. On the other hand, in order to improve the detection efficiency, K-means algorithm other than the blind search mechanism used in the original SSD model is exploited to find and determine the assignments of the sizes of default windows. For German traffic sign detection dataset, it obtains 97.1% mAP in detection accuracy and 0.07 s per image in detection efficiency. For Chinese traffic sign dataset, it obtains 89.7% mAP in detection accuracy and 0.08 s per image in detection efficiency. Compared with the original SSD model, the proposed model obtains the improved detection performance.