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The purpose of this paper is to investigate problems in performing stable lane changes and to find a solution to reduce energy consumption of autonomous electric vehicles.

An optimization algorithm, model predictive control (MPC) and Karush–Kuhn–Tucker (KKT) conditions are adopted to resolve the problems of obtaining optimal lane time, tracking dynamic reference and energy-efficient allocation. In this paper, the dynamic constraints of vehicles during lane change are first established based on the longitudinal and lateral force coupling characteristics and the nominal reference trajectory. Then, by optimizing the lane change time, the yaw rate and lateral acceleration that connect with the lane change time are limed. Furthermore, to assure the dynamic properties of autonomous vehicles, the real system inputs under the restraints are obtained by using the MPC method. Based on the gained inputs and the efficient map of brushless direct-current in-wheel motors (BLDC IWMs), the nonlinear cost function which combines vehicle dynamic and energy consumption is given and the KKT-based method is adopted.

The effectiveness of the proposed control system is verified by numerical simulations. Consequently, the proposed control system can successfully achieve stable trajectory planning, which means that the yaw rate and longitudinal and lateral acceleration of vehicle are within stability boundaries, which accomplishes accurate tracking control and decreases obvious energy consumption.

This paper proposes a solution to simultaneously satisfy stable lane change maneuvering and reduction of energy consumption for autonomous electric vehicles. Different from previous path planning researches in which only the geometric constraints are involved, this paper considers vehicle dynamics, and stability boundaries are established in path planning to ensure the feasibility of the generated reference path.

Real-time monitoring of the critical physical fields of core components in complex equipment is of great significance as it can predict potential failures, provide reasonable preventive maintenance strategies and thereby ensure the service performance of the equipment. This research aims to propose a hierarchical explicit–implicit combined sensing-based real-time monitoring method to achieve the sensing of critical physical field information of core components in complex equipment.

Sensor deployable and non-deployable areas are divided based on the dynamic and static constraints in actual service. An integrated method of measurement point layout and performance evaluation is used to optimize sensor placement, and an association mapping between information in non-deployable and deployable areas is established, achieving hierarchical explicit–implicit combined sensing of key sensor information for core components. Finally, the critical physical fields of core components are reconstructed and visualized.

The proposed method is applied to the spindle system of CNC machine tools, and the result shows that this method can effectively monitor the spindle system temperature field.

This research provides an effective method for monitoring the service performance of complex equipment, especially considering the dynamic and static constraints during the service process and detecting critical information in non-deployable areas.

The utilisation of building information modelling (BIM) technology is rapidly increasing among construction professionals across the world. Notwithstanding, recent studies revealed a low level of BIM implementation in the context of the Nigerian construction sector. Moreover, previous studies have established that BIM application comes with its share of various barriers. Therefore, this study aims to carry out an on-site survey on barriers to the application of BIM on construction sites in the Nigerian construction industry.

An extensive review of literature on BIM barriers was conducted, from where 33 factors were identified as significant BIM barriers peculiar to the developing countries. A questionnaire was developed and distributed to the targeted respondents, who are practicing professionals in the Nigerian construction industry, based on the identified barriers. The data collected were analysed by using both descriptive and inferential statistics.

The principal component analysis revealed that 27 barriers were peculiar to the Nigerian construction industry. The “lack of familiarity with BIM capacity, habitual resistance to change from the traditional style of design and build, and poor awareness of BIM benefit” were identified as the three most critical barriers hindering BIM application on construction sites in the Nigerian construction industry.

This study reveals key information on the peculiar barriers to BIM application in the Nigerian construction industry. The avoidance of these barriers will not only assist various construction stakeholders in the successful implementation of BIM application on a construction project but also promote information management systems and productivity within the construction industry to a great extent. These will further improve post-construction activities.

This study provides a substantial understanding of BIM state of the art in the context of barriers hindering BIM application on construction sites in the Nigerian construction industry.