KEYWORDS: Control systems, Batteries, Telecommunications, Research management, Fluctuations and noise, Temperature control, Thermal modeling, Safety, HVAC controls, Sensors
To address challenges such as the lengthy development cycle, poor system stability, and safety concerns in the control strategy development for thermal management in new energy vehicles, a thermal management system control strategy was designed using model-building and code generation techniques within the Simulink/Stateflow modeling environment. A control testing platform was constructed utilizing the panel functionality of the TSMaster virtual instrument simulation platform. Hardware TC1016P was employed to interface with the vehicle communication network, facilitating testing in conjunction with a specific new energy vehicle thermal management controller and a thermal management system test bench. Subsequent real vehicle thermal management tests were conducted to validate the performance of the control strategy model. The results indicate that the control strategy code generated from the model is fully compatible with the thermal management system of the new energy vehicle and demonstrates satisfactory performance during road tests.
To comprehensively monitor and protect lithium-ion battery packs, a design proposal for a Battery Management System (BMS) is introduced, utilizing domestically produced chips. The system is centered around the KF32A156 and MT9804 chips and employs a master-slave topology. Circuit designs for temperature, voltage, current acquisition, and balancing within the system units are developed. Software development for the KF32A156MQT microcontroller is conducted using the Chip ON IDE KF32 development environment, enabling functions such as voltage, current, and temperature monitoring, as well as balancing control. Validation of the system is performed through the construction of an experimental model. Experimental results demonstrate high precision, strong stability, and low production costs of the proposed design. Moreover, the utilization of domestically produced chips enhances the practical value significantly.
In order to address the issue of optimal pathfinding in autonomous mobile robot navigation, an improved path planning scheme based on the traditional A* algorithm is proposed. Firstly, aiming at the problem of collision and low planning search efficiency in traditional A* algorithm, a safety distance is set, and the Euclidean distance calculation method is selected in the heuristic function, constructing a cost function with dynamically adjustable heuristic function weights. Secondly, to smooth out the non-smooth paths generated by traditional A* algorithm, a Bezier curve smoothing algorithm is employed for path smoothing. Then, through simulation experiments, the significant improvements of the algorithm in terms of planning efficiency, safety, and path smoothness are verified. Finally, through autonomous navigation experiments, the feasibility of the improved A* algorithm is demonstrated. The research demonstrates that the algorithm designed in this paper can plan the optimal path and safely and efficiently reach the target point.
Analyze the encryption and decryption principle of KeeLoq and the shortcomings in security, propose an improvement scheme for KeeLoq algorithm to further improve its security; and conduct experimental verification by a BCM controller of a car, the experimental method is to combine the 027 service in the UDS protocol in KeeLoq algorithm to generate key authentication between the key side and the car side, the protocol generated temporary The key is passed with the factory key and serial number to derive a new password, and finally the key generation algorithm and the communication parties obtain the improved KeeLoq key in the learning process. The performance comparison with the original KeeLoq and triple KeeLoq algorithms concludes that while improving the security of the original algorithm, it reduces the complexity of the algorithm and increases the computation rate compared to triple KeeLoq. It is more suitable for PEPS system.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.