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This paper focuses on the design and test technique of an auxiliary power unit (APU) for a range-extended electric vehicle (RE-EV). The APU system is designed to improve RE-EV power and economy; it integrates the power system, generator system, battery system, and APU controller. The parameters of the APU parts are computed and optimized considering the vehicle power demand and the matching characteristic of the engine and generator. The hardware and software systems are developed for the APU-integrated control system. The APU test bench, combined with the displaying part, the control part, and the bench with its accessory, is constructed. Communication connection in the APU system is established by controller area network (CAN) bus. The APU controller outputs a corresponding signal to the engine control unit (ECU) and motor controller. To verify the rationality of the control strategy and the validity of the control logic, the engine speed control and integrated control experiment of the APU system are completed on the test bench. The test results showed that the test control system is reliable and the relevant control logic is in agreement with simulation analysis. The APU-integrated system could be well suited for application in RE-EVs.

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Based on the working characteristic of the engine and the generator, a coordination control strategy of Auxiliary Power Unit (APU) is studied for a rangeextended electric vehicle (RE-EV). A regulating rule of APU control system speed and torque which meets the power demand considering battery state of charge (SOC) of the RE-EV is designed. The PID and feedforward PID control methods of engine speed are discussed by simulation analysis, and the particle swarm optimization is adopted to optimize the PID parameters. The simulation results show that the feedforward PID control can stabilize the speed to 1600r/min in 1.5 seconds, and the overshoot can be ignored. In order to investigate the APU control processing, the incremental PID and feedback PID control algorithms are used to achieve speed control in the APU test bench. The influence on control period and the working condition are analysed from test results. The coordination control strategies of engine and generator are realized and verified by experimental research.

The penetration of unmanned aerial vehicles (UAVs) is an important aspect of UAV games. In recent years, UAV penetration has generally been solved using artificial intelligence methods such as reinforcement learning. However, the high sample demand of the reinforcement learning method poses a significant challenge specifically in the context of UAV games. To improve the sample utilization in UAV penetration, this paper innovatively proposes an improved sampling mechanism called task completion division (TCD) and combines this method with the soft actor critic (SAC) algorithm to form the TCD-SAC algorithm. To compare the performance of the TCD-SAC algorithm with other related baseline algorithms, this study builds a dynamic environment, a UAV game, and conducts training and testing experiments in this environment. The results show that among all the algorithms, the TCD-SAC algorithm has the highest sample utilization rate and the best actual penetration results, and the algorithm has a good adaptability and robustness in dynamic environments.

The penetration of unmanned aerial vehicles (UAVs) is an essential and important link in modern warfare. Enhancing UAV’s ability of autonomous penetration through machine learning has become a research hotspot. However, the current generation of autonomous penetration strategies for UAVs faces the problem of excessive sample demand. To reduce the sample demand, this paper proposes a combination policy learning (CPL) algorithm that combines distributed reinforcement learning and demonstrations. Innovatively, the action of the CPL algorithm is jointly determined by the initial policy obtained from demonstrations and the target policy in the asynchronous advantage actor-critic network, thus retaining the guiding role of demonstrations in the initial training. In a complex and unknown dynamic environment, 1000 training experiments and 500 test experiments were conducted for the CPL algorithm and related baseline algorithms. The results show that the CPL algorithm has the smallest sample demand, the highest convergence efficiency, and the highest success rate of penetration among all the algorithms, and has strong robustness in dynamic environments.

Rapidly completing the exploration and construction of unknown environments is an important task of a UAV cluster. However, the formulation of an online autonomous exploration strategy based on a real-time detection map is still a problem that needs to be discussed and optimized. In this paper, we propose a distributed unknown environment exploration framework for a UAV cluster that comprehensively considers the path and terminal state gain, which is called the Distributed Next-Best-Path and Terminal (DNBPT) method. This method calculates the gain by comprehensively calculating the new exploration grid brought by the exploration path and the guidance of the terminal state to the unexplored area to guide the UAV’s next decision. We propose a suitable multistep selective sampling method and an improved Discrete Binary Particle Swarm Optimization algorithm for path optimization. The simulation results show that the DNBPT can realize rapid exploration under high coverage conditions in multiple scenes.

Standing-up motion assistant machine is a new type of assistant device for the care and motion of the semi-disabled, which can replace the manual motion mode to a great extent and reduce the workload of the care-givers. After a detailed analysis of shortcomings of the structural design of the existing standing-up motion assistant machine in the practical application in elderly institutions, this paper proposes a design scheme and mechanical structure of the hanger. The optimized product is verified based on ergonomics theory. Results show that the design scheme and structure of the hanger of the motion assistant machine proposed in this paper can satisfy the requirements of occupant comfort on the premise of ensuring safety, as well as effectively expand the application of the standing-up motion assistant machine in elderly institutions of varied facility levels.