Making electrical driving systems cheaper, lighter, and more reliable is the consistent pursuit of current research and development. Mono-Inverter Multi-Permanent Magnet Synchronous Motor systems tend to share the static converters in electro-mechanical systems by connecting machines in parallel. This type of system has an obvious advantage in overall weight and cost. In this paper, we have proposed a new Maximum Torque Per Ampere (MTPA) control strategy for a MIMPMSM system, which supports three or more machines in parallel and works both in motor mode and brake mode. The calculation of the MTPA point minimizing the overall joule loss of the system is also given. The synchronization condition, stability, and optimal efficiency of the system are strictly proven. This new control structure is simple making current single PMSM systems easy to upgrade to support the MIMPMSM system. The experiment has demonstrated its feasibility, stability, and improvements in efficiency.

Although Unmanned Aerial Vehicles (UAVs)-aided wireless sensor networks (WSNs) have gained many applications, it is not for long that research works have been produced to define effective algorithms and protocols. In this article, we address the UAV-enabled WSN (U-WSN), explore the performance and the capability of the UAV, define the UAV functionalities as a communication node, and describe the architectures and the relevant typical technologies that emerge from this new paradigm. Furthermore, this article also identifies the main factors which influence the U-WSN design and analyzes the open issues and challenges in U-WSN. These insights may serve as motivations and guidelines for future designs of UAV-enabled WSNs.

In this work, we study data collection in multiple unmanned aerial vehicle (UAV)-aided mobile wireless sensor networks (WSNs). The network topology is changing due to the mobility of the UAVs and the sensor nodes, so the design of efficient data collection protocols is a major concern. We address such high dynamic network and propose two mechanisms: prioritized-based contact-duration frame selection mechanism (PCdFS), and prioritized-based multiple contact-duration frame selection mechanisms (PMCdFS) to build collision-free scheduling and balance the nodes between the multi-UAV respectively. Based on the two mechanisms, we proposed a Balance algorithm to conduct the collision-free communication between the mobile nodes and the multi-UAVs. Two key design ideas for a Balance algorithm are: (a) no need of higher priority for those nodes that have lower transmission rate between them and the UAV and (b) improve the communication opportunity for those nodes that have shorter contact duration with the UAVs. We demonstrate the performance of proposed algorithms through extensive simulations, and real experiments. These experiments using 15 mobile nodes at a path with 10 intersections and 1 island, present that network fairness is efficiently enhanced. We also confirm the applicability of proposed algorithms in a challenging and realistic scenario through numerous experiments on a path at Tongji campus in Shanghai, China.

Connecting two PMSMs in parallel to a 2-level 3-leg inverter gives a way to build up a high power-density driving system using existing electronic devices. But this type of system has a nature of nonlinearity that creates an obstacle in high performance control and the original system cannot be feedback-linearized directly. This article presents a reduced-order feedback-linearization method. In the first place, an extra order-reducing step that separates the system as a main system and an auxiliary system is applied. Then a feedback-linearization method is applied to the reduced-order system. With these effort, the original system can be converted into a linear time-invariant system bringing the controller design problem into the linear domain. In the last step, a linear robust state-feedback controller is used to achieve the speed control as well as compensate the unmeasurable external load torque. An extensive experiment is given to verify the feasibility and good performance in a highly unbalanced load torque situation of the designed controller.

Urban parks are vital public spaces that provide cultural ecosystem services (CESs) that enhance the well-being of city dwellers. As the demand for CESs has greatly increased, the imbalance between CES supply and demand has become prominent. Accurately identifying whether the supply of CESs meets the demand supports urban park planning and management. However, the CES supply–demand gap lies not only in the quantitative resource deficits, but also in the spatial mismatch between supply and demand. At present, scientific quantification methods for urban park CES supply and demand that comprehensively consider both quantitative and spatial relationships remain inadequate. To fill this gap, we propose an integrated framework that combines spatial and quantitative analysis to identify the supply and demand of urban park CESs, using Shanghai as the study area. The framework consists of three major steps: (1) mapping the CES supply and demand of urban parks; (2) identifying the CES supply–demand relationship by combining quantitative analysis through bivariate mapping with spatial analysis using spatial statistics; (3) categorizing the supply–demand relationship into four scenarios based on quantity balance and spatial matching, with three corresponding planning proposals. The results show that 136 sub-districts belong to the quantity balance and space matching type, while 79 sub-districts belonging to the imbalanced quantities type, including 41 belonging to the quantity imbalance and space mismatching type. Notably, only 15 sub-districts face a situation where supply is less than demand. Our findings provide a solid basis for identifying key areas of CES supply–demand conflict and prioritizing targeted planning interventions. This approach not only improves the efficiency of CES provision, but also addresses the growing demand for high-quality CESs in rapidly urbanizing regions.