Recent Patents on Engineering - Volume 17, Issue 2, 2023

Background: With the continuous development of science and technology, more and more human work has been replaced by robots because robots can do many jobs that human beings are not competent for. At present, researchers pay more and more attention to a new type of robot, the spherical robot. The most widely used spherical robot is the centroid deviation spherical robot. This paper mainly introduces the driving mode and structure of the spherical robot with centroid deviation. Objective: This paper explores the classification, development, advantages, and disadvantages of the driving modes of the spherical robot with centroid deviation. Methods: This paper reviews various products and patents related to centroid deviation spherical robot. This paper also introduces the structural characteristics, differences, and applications of the existing spherical robots with centroid deviation. Results: This paper compares and analyzes various spherical robots with centroid deviation, and their typical characteristics are summarized. This paper analyzes the main problems existing in various structures of the spherical robot, looks forward to the development trend of spherical robot, and discusses the research status and future of products and patents of the spherical robot. Conclusion: According to different driving modes, the spherical robot with centroid deviation can be divided into single pendulum drive, double pendulum drive, trolley drive, rolling body drive, and multi mass block drive. Among them, single pendulum drive, trolley drive, and rolling element drive are the most studied. At present, the structures of products and patents are similar, and the research direction has shifted from innovation to optimization.

Background: The Central China Rise Strategy is one of China’s important regional development strategies, and it has been officially implemented since 2006. Despite the obvious economic development resulting from the strategy, its impact on the environment remains unclear. Objective: Previous studies have focused more on the economic benefits of the Central China Rise Strategy while ignoring its environmental impact. This paper focuses on the environmental benefits and aims to promote the coordinated development between the economy and the environment. Methods: Panel data of 30 Chinese provinces from 2000 to 2017 were selected to construct a propensity score matching-difference-in-difference (PSM-DID) framework for systematic research that includes benchmark modeling, as well as dynamic effect and mechanism analyses. Results: 1) The benchmark model and placebo test proved that the Central China Rise Strategy had increased environmental pollution. 2) Dynamic effect analysis revealed that the impact of the Central China Rise Strategy on environmental pollution has gradually increased in the short- and medium- term, with 2012 exhibiting the greatest augmentation, significantly reducing from 2016 onwards. 3) The mechanism of action considers three mechanisms. The level of economic development is a path through which the Central China Rise Strategy leads to the aggravation of environmental pollution while the city size is not. Foreign direct investment has improved environmental pollution. Conclusion: The Central China Rise Strategy has aggravated environmental pollution, especially in the short and medium-term. In view of the mechanism path, we put forward three targeted suggestions. In the future, we will study some of the limitations of this paper: more mechanisms of action will be considered, and the use of new technologies, such as neural networks, will be compared with our results.

Background: Automobile anti-lock braking system (ABS) is an important part of the vehicle active safety control system, which is widely used in all kinds of vehicles. At present, the research of ABS mainly focuses on the study of the control algorithm, which is intended to improve the stability, robustness, and adaptability of the control algorithm. Objective: ABS control algorithm has become a research hotspot. Different researchers have proposed different control algorithms and patents because of the different tools used and the entry points of the research. These control algorithms have played a role in promoting the development of ABS. This article reviews various control algorithms. Methods: According to the research status of domestic and foreign researchers in the field of ABS control algorithms, ABS control algorithms are mainly divided into two categories: control methods based on logic thresholds and control methods based on slip ratio. Results: The comparative study of ABS control methods shows that the logic threshold control method has strong maneuverability and simple implementation, but its adaptability is poor. Sliding mode control has strong robustness and good transient response, but chattering needs to be suppressed. Although the PID control algorithm is simple and easy to implement, it needs to improve the transient response of the system. Conclusion: In the future, it is necessary to explore adaptive robust control algorithms that adapt to extreme conditions such as high nonlinearity and sudden road changes, such as active disturbance rejection control technology, deep learning neural network control technology, etc.

Background: Nowadays, with the increase of the number of cars, traffic accidents occur frequently, improving the active safety of cars, and traffic safety has become an inevitable requirement of the development of intelligent transportation. Objective: Motion planning for autonomous driving is a challenging problem due to the uncertainty of the unknown complex environment. Conventional methods may fail in some cases on account of poor real-time performance and instability. The objective is to propose a motion planning method to plan a reasonable path autonomously for an autonomous vehicle in unknown environments and ensure obstacle avoidance. Methods: The solution is to use the improved Glasius Bio-inspired Neural Network (GBNN) to plan a feasible route for the autonomous vehicle, which adaptively changes the direction of movement according to the changes of neuron values. Neuron connection weight in the neural network is reasonably improved to increase the update rate of activity value, so that this model can more adapt to the changes of dynamic environment. Meanwhile, the planned trajectory is fitted to meet vehicle kinematics model. Results: Unstructured and structured roads are tested in static and dynamic environments respectively. During the test, static obstacles and surrounding vehicles’ intentions are all generated randomly. In this way, the generated route can be optimal and adapt to the stochastic as well. Conclusion: Simulation results in unstructed road and structed road show the effectiveness of the proposed algorithm in autonomous motion planning. In addition, the performance of path length, smoothness and turning angle has been improved.

Aims and Objectives: The stability control of the four-wheel hub motor-driven electric vehicle is of great significance to the safety of the driver during the driving process, and the torque fluctuation is an important factor that affects the stability control of the vehicle. Therefore, this paper reviews the key technologies and difficulties of torque ripple suppression for in-wheel motor-driven electric vehicles from two aspects: rational design of the in-wheel motor structure to suppress the torque fluctuation of the motor and the in-wheel motor torque control distribution strategy. Methods: Through the analysis of the structural characteristics of the motor, the structural optimization design of the pole slot, cogging, core shape, and magnetic pole shape is used to suppress the torque fluctuation of the motor, and the methods of previous scholars are unified and explained; From the motor control strategy, summed up the scholars in the motor torque ripple suppression method strategy; From the perspective of motor torque control allocation strategy, a series of related strategies are elaborated. The previous researchers proposed the neural network PID electronic differential speed torque comprehensive control strategies, electronic differential control algorithms based on sliding mode control, automotive electronic stability program control algorithms based on hierarchical coordinated control strategies, and other control strategies and algorithms. Results: Based on the theoretical model, the theoretical model is verified and tested through software simulation or test platform. The errors of all simulation and test results in the literature and the theoretical model are within the acceptable range. Conclusion: The theoretical model has been verified on the software simulation or test platform, which proves the feasibility and effectiveness of the theoretical model, thereby suppressing torque fluctuations and improving the stability of the vehicle. Finally, the development direction of the key technology of torque ripple suppression for four-wheel in-wheel motor-driven electric vehicles has been prospected.

Aim: The proposed work aim was to monitor real-time attendance using face recognition in every institutional sector. It is one of the key concerns in every organization. Background: Nowadays, most organizations spend a lot of time marking attendance for a large number of individuals manually. Many technologies like Radio Frequency Identification (RFID) and biometric systems are introduced to overcome the manual attendance system. when using these RFID and biometric people need to stand in queue to make their presence. Objective: The main objective of the system is to provide an automated attendance system with the help of face recognition owing to the difficulty in the manual as well as other traditional attendance systems. Methods: The proposed work was done through face recognition using Machine Learning. Face recognition is a part of biometric characteristic of a human. It was easy to process than other biometric measurements like fingerprint, iris scan, hand scan, retina scan. The Haarcascade classifier will detect a face, and the LBPH algorithm will recognize the face. The experiment performs on the creation of real-time face data. Results: Using the web camera connected to the computer, face detection and recognition are performed, and recognized faces mark as attended. Here, the admin module and teacher modules are implemented with different functionalities to monitor attendance. Conclusion: Experiment results get 94.5% accuracy in face detection and 98.5% accuracy in face recognition by using the Haarcascade classifier and LBPH algorithm. This application system will be simple to implement, accurate, and efficient in monitoring attendance in real-time.

Background: The mechanical properties of the soil are key factors for studying the ground adhesion capability of high-speed tracked vehicles under the action of dynamic loads. Classic mechanical models of ground surface soil are insufficient to predict the mobility of high-speed tracked vehicles. Objectives: The aim was to study a soil mechanical model for deformable grounds under the dynamic action of high-mobility tracked vehicles. Methods: According to the high loading and shear rate of high-speed heavy-duty tracked vehicles, a three-dimensional soil simulation model for deformable grounds was established. Numerical calculations were performed. Results: The correctness of the simulation model was validated through the comparison of the numercal calculation results with the soil-bin test results. Conclusion: On the basis of the empirical pressure-sinkage and the Janosi shear model of ground surface soil, and coupled with factors such as the loading and shear rate, a new improved mechanical model of ground surface soil was built for the running conditions of high-speed heavy-duty tracked vehicles. The correctness of the improved model was validated through the comparison of the calculation results of the improved model with the numerical simulation results, which provides a basis for studying the driving performance of high-speed heavy-duty tracked vehicles on deformable grounds.

Background: Precision plastic forming technology has become an important development direction of advanced manufacturing technology because of its remarkable characteristics of high yield, high quality, and low consumption. Compared with traditional forming technology, it not only improves the utilization rate of metal materials, but also strengthens the dimensional accuracy of the workpiece. Therefore, the development trend of metal plastic precision forming technology has been paid increasing attention. Objective: To meet the increasing requirement of processing quality and processing efficiency in the metal precision plastic forming technology, metal cold precision plastic forming technology, metal warm precision plastic forming technology, metal thermal precision plastic forming technology and metal composite precision plastic forming technology is being improved continuously. Methods: This paper reviews the current various representative patents related to metal cold precision plastic forming technology, metal warm precision plastic forming technology, metal thermal precision plastic forming technology, and metal composite precision plastic forming technology. Results: Through investigating a large number of patents on metal precision plastic forming, metal cold precision plastic forming technology, metal warm precision plastic forming technology, metal thermal precision plastic forming technology and metal composite precision plastic forming technology are discussed. Conclusion: The optimization of metal precision plastic forming is conducive to increasing processing efficiency and processing quality. More relevant patents will be invented in the future.