Design and Implementation of a Battery Big Data Platform Through Intelligent Connected Electric Vehicles

The development of a battery management algorithm is highly dependent on high-quality battery operation data,especially the data in extreme conditions such as low temperatures.The data in faults are also essential for failure and safety management research.This study developed a battery big data platform to realize vehicle operation,energy interaction and data management.First,we developed an electric vehicle with vehicle navigation and position detection and designed an environmental cabin that allows the vehicle to operate autonomously.Second,charging and heating systems based on wireless energy transfer were developed and equipped on the vehicle to investigate optimal charging and heating methods of the batteries in the vehicle.Third,the data transmission network was designed,a real-time monitoring interface was developed,and the self-developed battery management system was used to measure,collect,upload,and store battery operation data in real time.Finally,experimental validation was performed on the platform.Results demonstrate the efficiency and reliability of the platform.Battery state of charge estimation is used as an example to illustrate the availability of battery operation data.

Design and application of electrical fire monitoring system in mining industry

To protect mining areas from electrical fire, it is very important to install electrical nre momtormg system to ensure safety in development of mineral resources and for buildings. In this paper, design for electrical fire monitoring and detection system with optional sensor modules has been proposed. In addition, necessity and suitability of electrical fire monitoring and detection system with optional sensor modules in mining areas have been reviewed. The designed electrical fire monitoring and detection system suit- able for work environment of mining industry is composed by host-computer monitoring software and slave-computer detectors. Monitoring detectors are manufactured by using embedded technology. Exter- nal shells deployed have superior enclosure performances and explosion-proof properties. It is easy to install and maintain the system. In general, the system has reached, or even exceeded standards specified in national standards for performances and appearances of such devices. Test results show application of electrical fire monitoring and detection system can effectively enhance monitoring intensity over the mining areas and provide reliable guarantee to ensure orderly development of mineral resources and to protect physical and property safety of citizens in these areas.

Effect of CF and RPP on the Mechanical and Electrical Properties of Smart Aggregate

By using redispersible polymer powder（RPP） and carbon fiber（CF） to adjust the flexibility and electrical properties of the smart aggregate, a new kind of smart aggregate with Z type structure was proposed. The study shows that Z type aggregate is more sensitive to the feedback of external force than the prism aggregate in the same loading environment, and it indicates that Z type aggregate is more suitable for the research and application of concrete health monitoring. Although the incorporation of RPP would cause the compressive strength of the aggregates and the elastic modulus of hardened cement mortar to reduce slightly within the dosage of RPP by 2.25% because of the polymer film formed in the internal system, this would improve the deformability of the aggregates. In the early loading stage（in the first 60 seconds）, the intelligent concrete specimens implanted with Z type smart aggregate do not show higher sensitivity as expected, although the resistance change rate changes a little bit more, the overall of it is still in balance. Adding RPP could improve the flexibility of smart aggregates exactly, and it plays an active role in prolonging the life of the smart aggregates. By implanting Z type aggregates the damage and failure of the concrete structure could be predicted accurately in this study. The results of this paper will help to promote further research and application of intelligent concrete.

Call for Papers Journal of Electronic Science and Technology Special Section on Energy-Efficient Technologies—Crowd Energy Applications

Since decades,the global electricity demand shows only one direction：a considerable constant increase every year.But the unlimited growth in energy consumption is discussed increasingly critical,not only primarily in terms of limitations but also in terms of more efficient,more intelligent,and more sustainable usage of energy.Energy-efficient technologies（EET）and renewable energy technologies are already in a competitive position in different markets,and they are also activelyembedded in scientific research. Meanwhile, enormous research on key points, such as smart home, smart cities, smart environments, and smart living in general, have been executed. Applying EET to improve human well-being and to reduce energy and resource consumption is on focus.

Lateral stability regulation of intelligent electric vehicle based on model predictive control

Purpose–This paper studies the lateral stability regulation of intelligent electric vehicle(EV)based on model predictive control(MPC)algorithm.Design/methodology/approach–Firstly,the bicycle model is adopted in the system modelling process.To improve the accuracy,the lateral stiffness of front and rear tire is estimated using the real-time yaw rate acceleration and lateral acceleration of the vehicle based on the vehicle dynamics.Then the constraint of input and output in the model predictive controller is designed.Soft constraints on the lateral speed of the vehicle are designed to guarantee the solved persistent feasibility and enforce the vehicle’s sideslip angle within a safety range.Findings–The simulation results show that the proposed lateral stability controller based on the MPC algorithm can improve the handling and stability performance of the vehicle under complex working conditions.Originality/value–The MPC schema and the objective function are established.The integrated active front steering/direct yaw moments control strategy is simultaneously adopted in the model.The vehicle’s sideslip angle is chosen as the constraint and is controlled in stable range.The online estimation of tire stiffness is performed.The vehicle’s lateral acceleration and the yaw rate acceleration are modelled into the two-degree-of-freedom equation to solve the tire cornering stiffness in real time.This can ensure the accuracy of model.