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Probabilistic-Ellipsoid Hybrid Reliability Multi-Material Topology Optimization Method Based on Stress Constraint

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Computer Modeling in Engineering & Sciences 2024年第7期140卷 757-792页

作者： Zibin Mao qinghai zhao Liang Zhang College of Mechanical and Electrical Engineering Qingdao UniversityQingdao266071China National Engineering Research Center for Intelligent Electrical Vehicle Power System Qingdao UniversityQingdao266071China

This paper proposes a multi-material topology optimization method based on the hybrid reliability of the probability-ellipsoid model with stress constraint for the stochastic uncertainty and epistemic uncertainty of mechanical loads in optimization *** probabilistic model is combined with the ellipsoidal model to describe the uncertainty of mechanical *** topology optimization formula is combined with the ordered solid isotropic material with penalization(ordered-SIMP)multi-material interpolation *** stresses of all elements are integrated into a global stress measurement that approximates the maximum stress using the normalized p-norm ***,the sequential optimization and reliability assessment(SORA)is applied to transform the original uncertainty optimization problem into an equivalent deterministic topology optimization(DTO)*** response surface and sparse grid technique are combined with SORA to get accurate information on the most probable failure point(MPP).In each cycle,the equivalent topology optimization formula is updated according to the MPP information obtained in the previous *** adjoint variable method is used for deriving the sensitivity of the stress constraint and the moving asymptote method(MMA)is used to update design ***,the validity and feasibility of the method are verified by the numerical example of L-shape beam design,T-shape structure design,steering knuckle,and 3D T-shaped beam.

关键词： Stress constraint probabilistic-ellipsoid hybrid topology optimization reliability analysis multi-material design

Topology Optimization of Transient Thermo-elastic Structure Considering Regional Temperature Control

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Acta Mechanica Solida Sinica 2023年第2期36卷 262-273页

作者： Jianliang Chen qinghai zhao Liang Zhang Kaiyu Ma College of Mechanical and Electrical Engineering Qingdao UniversityQingdao 266071China National Engineering Research Center for Intelligent Electrical Vehicle Power System Qingdao UniversityQingdao 266071China

In this paper,a topology optimization model for transient thermo-elastic coupling problems is *** on the method of solid isotropic material with penalization,the coupled equations of transient thermomechanical field are *** this model,the objective is to minimize the global structural compliance with volume and maximum temperature constraints during the working *** efficiently restrict the maximum temperature of the transient thermo-elastic structure in time and spatial dimensions,the regional temperature control scheme is constructed using the aggregation *** adjoint variable method is adopted to derive the sensitivity of objective function and constraints,and the design variables are updated through the method of moving asymptotes to obtain clear optimal *** effects of the duration and magnitude of the thermal and structural loads on the optimization results are discussed through several numerical examples.

关键词： Topology optimization Transient thermo-elastic problems Temperature constraints Aggregation function

Robust Topology Optimization of Vehicle Suspension Control Arm

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Journal of Beijing Institute of Technology 2019年第3期28卷 626-634页

作者： Xiaokai Chen Cheng Zhang qinghai zhao School of Mechanical Engineering Beijing Institute of TechnologyBeijing 100081China National and Local Union Engineering Research Center of Electric Vehicle Intelligent Power Integration Technology Qingdao UniversityQingdao 266071ShandongChina

A robust topology optimization design framework is developed to solve lightweight structural design problems under uncertain conditions. To enhance the calculation accuracy and flexibility of the statistical moments of robust analysis, number theory integral method is applied to sample point selection and weight assignment. Both the structure topology optimization and number theory integral methods are combined to form a new robust topology optimization method. A suspension control arm problem is provided as a demonstration of robust topology optimization methods under loading uncertainties. Based on the results of deterministic and robust topology optimization, it is demonstrated that the proposed robust topology optimization method can produce a more robust design than that obtained by deterministic topology optimization. It is also found that this new approach is easy to apply in the existing commercial topology optimization software and thus feasible in practical engineering problems.

关键词： robust topology optimization (RTO) number theory integral suspension control arm uncertainty deterministic topology optimization (DTO)

Deep Learning Based Automatic Charging Identification and Positioning Method for Electric Vehicle

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Computer Modeling in Engineering & Sciences 2023年第9期136卷 3265-3283页

作者： Hao Zhu Chao Sun Qunfeng Zheng qinghai zhao School of Mechanical and Electrical Engineering Qingdao UniversityQingdao266071China School of Mechanical Engineering Beijing Institute of TechnologyBeijing100081China National Engineering Research Center for Intelligent Electrical Vehicle Power System Qingdao UniversityQingdao266071China

Electric vehicle charging identification and positioning is critically important to achieving automatic *** terms of the problem of automatic charging for electric vehicles,a dual recognition and positioning method based on deep learning is *** method is divided into two parts:global recognition and localization and local recognition and *** the specific implementation process,the collected pictures of electric vehicle charging attitude are classified and *** is trained with the improved YOLOv4 networkmodel and the corresponding detectionmodel is *** contour of the electric vehicle is extracted by the BiSeNet semantic segmentation *** minimum external rectangle is used for positioning of the electric *** on the location relationship between the charging port and the electric vehicle,the rough location information of the charging port is *** automatic charging equipment moves to the vicinity of the charging port,and the camera near the charging gun collects pictures of the charging *** model is detected by the Hough circle,the KM algorithmis used for featurematching,and the homography matrix is used to solve the *** results show that the dual identification and location method based on the improved YOLOv4 algorithm proposed in this paper can accurately locate the charging *** accuracy of the charging connection can reach 80%.It provides an effective way to solve the problems of automatic charging identification and positioning of electric vehicles and has strong engineering practical value.

关键词： Electric vehicle automatic charging identification and positioning deep learning

Robust Topology Optimization of Periodic Multi-Material Functionally Graded Structures under Loading Uncertainties

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Computer Modeling in Engineering & Sciences 2021年第5期127卷 683-704页

作者： Xinqing Li qinghai zhao Hongxin Zhang Tiezhu Zhang Jianliang Chen College of Mechanical and Electrical Engineering Qingdao UniversityQingdao266071China Power Integration and Energy Storage System Engineering Technology Center Qingdao UniversityQingdao266071China

This paper presents a robust topology optimization design approach for multi-material functional graded structures under periodic constraint with load *** characterize the random-field uncertainties with a reduced set of random variables,the Karhunen-Lo`eve(K-L)expansion is *** sparse grid numerical integration method is employed to transform the robust topology optimization into a weighted summation of series of deterministic topology *** dividing the design domain,the volume fraction of each preset gradient layer is *** on the ordered solid isotropic microstructure with penalization(Ordered-SIMP),a functionally graded multi-material interpolation model is formulated by individually optimizing each preset gradient *** periodic constraint setting of the gradient layer is achieved by redistributing the average element compliance in ***,the method of moving asymptotes(MMA)is introduced to iteratively update the design *** numerical examples are presented to verify the validity and applicability of the proposed *** results demonstrate that the periodic functionally graded multi-material topology can be obtained under different numbers of sub-regions,and robust design structures are more stable than that indicated by the deterministic results.

关键词： Multi-material topology optimization robust design periodic functional gradient sparse grid method

An Efficient Strategy for Non-probabilistic Reliability-Based Multi-material Topology Optimization with Evidence Theory

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Acta Mechanica Solida Sinica 2019年第6期32卷 803-821页

作者： qinghai zhao Hongxin Zhang Tiezhu Zhang Qingsong Hua Lin Yuan Wenyue Wang National and Local Union Engineering Research Center of Electric Vehicle Intelligent Power Integration Technology Qingdao UniversityQingdao 266071China Mechanical and Electrical College Qingdao UniversityQingdao 266071China

It is essential to consider the effects of incomplete measurement,inaccurate information and inadequate cognition on structural topology *** the multi-material structural topology optimization with non-probability uncertainty,the multi-material interpolation model is represented by the ordered rational approximation of mat erial properties(ordered RAMP).Combined with structural compliance minimization,the multi-material topology optimization with reliability constraints is *** corresponding non-probability uncertainties are described by the evidence theory,and the uniformity processing method is introduced to convert the evidence variables into random *** first-order reliability method is employed to search the most probable point under the reliability index constraint,and then the random variables are equivalent to the deterministic variables according to the geometric meaning of the reliability index and sensitivity ***,the non-probabilistic reliability-based multi-material topology optimization is transformed into the conventional deterministic optimization format,followed by the ordered RAMP method to solve the optimization ***,through numerical examples of 2D and 3D structures,the feasibility and effectiveness of the proposed method are verified to consider the geometrical dimensions and external loading uncertainties.

关键词： Multi-material Topology optimization Non-probabilistic Reliability Evidence theory

Improved RRT^(∗)Algorithm for Automatic Charging Robot Obstacle Avoidance Path Planning in Complex Environments

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Computer Modeling in Engineering & Sciences 2023年第12期137卷 2567-2591页

作者： Chong Xu Hao Zhu Haotian Zhu Jirong Wang qinghai zhao College of Mechanical and Electrical Engineering Qingdao UniversityQingdao266071China School of Arts and Sciences University of PennsylvaniaPhiladelphiaPA 19104USA National Engineering Research Center for Intelligent Electrical Vehicle Power System Qingdao UniversityQingdao266071China

A new and improved RRT∗algorithm has been developed to address the low efficiency of obstacle avoidance planning and long path distances in the electric vehicle automatic charging robot *** algorithm enables the robot to avoid obstacles,find the optimal path,and complete automatic charging *** maintains the global completeness and path optimality of the RRT algorithmwhile also improving the iteration speed and quality of generated paths in both 2D and 3D path *** finding the optimal path,the B-sample curve is used to optimize the rough path to create a smoother and more optimal *** comparison experiments,the new algorithmyielded reductions of 35.5%,29.2%,and 11.7%in search time and 22.8%,19.2%,and 9%in path length for the 3D ***,experimental validation of the automatic charging of electric vehicles was conducted to further verify the effectiveness of the *** simulation experimental validation was carried out by kinematic modeling and building an experimental *** error between the experimental results and the simulation results is within 10%.The experimental results show the effectiveness and practicality of the algorithm.

关键词： Path planning RRT∗ deep learning obstacle avoidance

Composite Braking Control Strategy for Electromechanical-Hydraulic Vehicles

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CSEE Journal of Power and Energy Systems 2024年第4期10卷 1722-1732页

作者： Zewen Meng Jichao Hong Hongxin Zhang Tiezhu Zhang Xiaoming Xu qinghai zhao Jian Yang College of Mechanical and Electrical Engineering Qingdao UniversityQingdao 260071China Power Integration and Energy Storage Systems Engineering Technology Center(Qingdao) Qingdao 260071China School of Mechanical Engineering University of Science and Technology BeijingBeijing 100083China Shunde Graduate School of University of Science and Technology Beijing Foshan 528000China

Short driving ranges and low braking energy recovery efficiencies are two recognized technical bottlenecks to be overcome in electric vehicles. In this paper, a novel electromechanical-hydraulic coupling system is proposed and integrated as a powertrain for electric vehicles, which can assist the electric vehicle to fully utilize its braking energy. The hydraulic regenerative braking force and electric regenerative braking force can provide all the braking needs using the medium and small braking intensities. Furthermore, an improved compound brake control strategy based on the braking force distribution is proposed and simulated. The results show that under the premise of ensuring braking stability, the electromechanical-hydraulic coupling driving electric vehicle can adapt to various working conditions with excellent energy-saving results. The hydraulic accumulator recovery efficiency is above 99%, and the state of charge consumption rate of the battery pack can be reduced by more than 9%. More importantly, the proposed hybrid power system can significantly improve the driving range and energy efficiency, as well as reduce the consumers' mileage anxiety in electric vehicles.

关键词： Braking control strategy electric vehicle electromechanical-hydraulic coupling energy recovery state of charge

An Analytical Review of EU Strategy for a New Partnership with Central Asia

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China International Studies 2007年第3期27卷 58-72页

作者： zhao qinghai Associate Research Fellow at China Institute of International Studies.

On June 22,2007,the Council of the European Union ratified its strategy paper for Central Asia drafted by the rotating presidency Germany. German foreign minister Frank-Walter Steinmeier presented the document to the ... 详细信息

关键词：欧盟中亚伙伴关系德国