Land Vehicle Research Articles

Neural Network-Based Descent Control for Landers with Sloshing and Mass Variation: A Cascade and Adaptive PID Strategy

Autonomous control of lunar landers is essential for successful space missions, where precision and efficiency are crucial. This study presents a novel control strategy that leverages proportional, integral, and derivative (PID) controllers to manage the altitude, attitude, and position of a lunar lander, considering time-varying mass and sloshing behavior. Additionally, neural network models are developed, to approximate the lander’s mass properties as they change during descent. The challenge lies in the significant mass variations due to fuel, oxidizer, and pressurant consumption, which affect the lander’s inertia and sloshing behavior and complicate control efforts. We have developed a control-oriented model incorporating these mass dynamics, employing multiple PID controllers to linearize the system and enhance control precision. Altitude is maintained by one PID controller, while two others adjust the thrust vector control (TVC) gimbal angles to manage pitch and roll, with a fourth controller governing yaw via a reaction control system (RCS). A cascade PD controller further manages position by feeding commands to the attitude controllers, ensuring the lander reaches its target location. The lander’s TVC mechanism, equipped with a spherical gimbal, provides thrust in the desired direction, with control angles α and β regulated by the PID controllers. To improve the model’s accuracy, we have introduced time delays caused by fluid dynamics and actuator response, modeled via computational fluid dynamics (CFD). Fluid sloshing effects are also simulated as external forces acting on the lander. The neural networks are trained using data derived from computer-aided design (CAD) simulations of the lander vehicle, specifically the inertia tensor and the center of mass (COM) based on the varying mass levels in the tanks. The trained neural networks (NNs) can then use lander tank levels and orientation to inform and accurately predict the lander’s COM and inertia tensor in real time during the mission. The implications of this research are significant for future lunar missions, offering enhanced safety and efficiency in vehicle descent and landing operations. Our approach allows for real-time estimation of the lander’s state and for precise execution of maneuvers, verified through complex numerical simulations of the descent, hover, and landing phases.

Noise assessment of multirotor configurations during landing proceduresa).

This study numerically investigates the noise impact of multirotor aerial vehicles with different rotor scales during landing procedures. The operational environments of individual rotors are influenced by rotational speed and wake dynamics, leading to variations in landing noise characteristics. Noise impacts are evaluated across various landing operations from both physical and psychoacoustic perspectives using noise source hemispheres and noise maps. The physical noise impact is quantified using sound exposure level (SEL), while the psychoacoustic impact is assessed through a psychoacoustic annoyance (PA) based on sound quality metrics. Performance contours are established to compare noise impacts alongside other factors, such as energy consumption, landing duration, vehicle attitudes, and safety considerations. The combined effect of noise source strength and landing duration determines SEL, while PA is primarily influenced by acoustic loudness, which follows a similar trend to noise source strength. Consequently, physical and psychoacoustic noise impacts exhibit distinct trends based on the landing operations. This study outlines a process for optimizing landing operations that meet predefined performance goals while minimizing noise impacts. Because operational performance varies significantly across different landing procedures and vehicle types, the study emphasizes the importance of incorporating comprehensive performance criteria in the design of landing operations.

Cycle slip detection and repair method towards multi-frequency BDS-3/INS tightly coupled integration in kinematic surveying

Carrier phase integer ambiguities must be determined for BDS-3/inertial navigation system (INS) tightly coupled (TC) integration to achieve centimetre-level positioning accuracy. However, cycle slip breaks the consistency of the integer ambiguities. Conventional multi-frequency cycle slip methods use the pseudorange; thus, requiring improvement when applied to kinematic situations. Furthermore, a concise and nonprior information-dependent model is crucial for real-time processing. In this study, an inertial-aided BDS-3 cycle slip detection and repair (I-CDR) method was developed. First, a BDS-3/INS TC model with I-CDR was created. The ionospheric delays were modelled as part of the TC states; therefore, they could be estimated and eliminated. Investigations were conducted on the effects of carrier phase noise, residual ionosphere delay, and INS-predicted position error on combined cycle slip detection (CCD) accuracy. The optimal CCDs under various frequency available configurations were determined. The effectiveness of I-CDR was demonstrated using land vehicle test data. The false alarm ratio was less than 1.0%, and the missed detection ratio was almost zero even in situations with challenging abundant 1-cycle slips in random epochs. Furthermore, the right determination ratio reached 100%. In addition, BDS-3 signal loss-recovery cases were simulated, and all cycle slips for all satellites could be repaired within 40s. I-CDR exhibits outstanding cycle slip detection and repair performance for dense 1-cycle slip and signal loss-recovery cases, demonstrating its suitability for BDS-3/INS TC integration.

Four-Dimensional Generalized AMS Optimization Considering Critical Engine Inoperative for an eVTOL

In this paper, we present a method to optimize the attainable moment set (AMS) to increase the control authority for electrical vertical take-off and landing vehicles (eVTOLs). As opposed to 3D AMSs for conventional airplanes, the hover control of eVTOLs requires vertical thrust produced by the powered lift system in addition to three moments. The limits of the moments and vertical thrust are coupled due to input saturation, and, as a result, the concept of the traditional AMS is extended to the 4D generalized moment set to account for this coupling effect. Given a required moment set (RMS) derived from system requirements, the optimization is formulated as a 4D convex polytope coverage problem, i.e., the AMS coverage over the RMS, such that the system’s available control authority is maximized to fulfill the prescribed requirements. The optimization accounts for not only nominal flight, but also for one critical engine inoperative situation. To test the method, it is applied to an eVTOL with eight rotors to optimize for the rotors’ orientation with respect to the body axis. The results indicate highly improved coverage of the RMS for both failure-free and one-engine-inoperative situations. Closed-loop simulation tests are performed for both optimal and non-optimal configurations to further validate the results.

Design approach for tilt propellers of UAM/eVTOLs for cruise and hover considering aerodynamic and aeroacoustic characteristics via a multi-fidelity model

The design of quiet and efficient propellers/rotors is driven by the rapid development of Vertical Takeoff and Landing (VTOL) vehicles in urban areas. However, this task is challenging due to the expensive computational cost of propeller aerodynamic and aeroacoustic optimization based on accurate high-fidelity (HF) models. In contrast, many low-fidelity (LF) methods are less costly but also less accurate for complex propeller blade geometries, such as those involving sweep. This work aims to use a multi-fidelity (MF) surrogate model (SM) that combines a small HF data set for accuracy and a larger LF data set to speed up modeling. The MF approach inherits the accuracy of the HF method while retaining the computational efficiency of the LF model. The HF and LF aerodynamic data sets for training the MF model are obtained from a RANS solver and a meshless Large Eddy Simulation (LES) method, respectively. The obtained surface pressure of the blade is then used to calculate the noise signals radiating from the propeller using a Farassat's Formulation 1A (F1A) code. For practical design, we developed an optimization framework that combines these aerodynamic and aeroacoustic solvers, the MF model, design of experiment (DoE), and a multi-objective optimizer. The framework aims to optimize the blade aerodynamic shape in terms of chord, twist, and sweep distributions along the span from a baseline propeller, with objectives of efficiency and noise reduction under thrust constraints for both cruise and hover operating conditions. The obtained optimal designs, in the form of three-dimensional Pareto fronts, increased the aerodynamic efficiency by approximately 2% for cruise and 5% for hover and decreased the overall sound pressure level (OASPL) for hover by about 4 dB from the baseline propeller. The MF surrogate model, which utilizes both HF and LF data, doubled the optimization efficiency compared to the surrogate model based solely on HF data. Furthermore, the model based only on LF data fails to capture the three-dimensional flow effects induced by propeller sweep, which is crucial for reducing propeller noise. The aerodynamic benefits include reduced flow separation near the blade root during hover and more ideal loading distribution during cruise, while the aeroacoustic improvements are demonstrated through the “dephase” effect on noise signals emitted from different parts of the swept blade.

Coupling of Advanced Guidance and Robust Control for the Descent and Precise Landing of Reusable Launchers

This paper investigates the coupling of successive convex optimization guidance with robust structured H∞ control for the descent and precise landing of Reusable Launch Vehicles (RLVs). More particularly, this Guidance and Control (G&C) system is foreseen to be integrated into a nonlinear six-degree-of-freedom RLV controlled dynamics simulator which covers the aerodynamic and powered descent phase until vertical landing of a first-stage rocket equipped with a thrust vector control system and steerable planar fins. A cost function strategy analysis is performed to find out the most efficient one to be implemented in closed-loop with the robust control system and the vehicle flight mechanics involved. In addition, the controller synthesis via structured H∞ is thoroughly described. The latter are built at different points of the descent trajectory using Proportional-Integral-Derivative (PID)-like structures with feedback on the attitude angles, rates, and lateral body velocities. The architecture is verified through linear analyses as well as nonlinear cases with the aforementioned simulator, and the G&C approach is validated by comparing the performance and robustness with a baseline system in nominal conditions as well as in the presence of perturbations. The overall results show that the proposed G&C system represents a relevant candidate for realistic descent flight and precise landing phase for reusable launchers.

Distributed minimum error entropy with fiducial points Kalman filter for state tracking

With the growing size of the system, this distributed Kalman filter (DKF) is widely used in multi-sensor networks. However, it is difficult for DKF to accurately estimate state values in non-Gaussian noise environments. In this paper, a regression equation is first constructed to contain all sensor node information. Then, by bringing the minimum error entropy with fiducial points (MEEF) standard into the process of information fusion, a robust algorithm named centralized MEEF KF (CMEEF-KF) is presented, which is robust to non-Gaussian noise and unusual data. Furthermore, to overcome the communication burden of CMEEF-KF in sensor networks, the distributed MEEF-KF (DMEEF-KF) is developed, which construct a framework of consensus average method for node information fusion. Specifically, each sensor only exchanges the key information with its neighborhoods. In addition, in order to make the algorithm able to cope with the nonlinear state estimation problem, the distributed MEEF extended Kalman filter is also proposed. Eventually, the effectiveness of the suggested algorithms is demonstrated by land vehicle navigation and power system tracking state estimation using a 10-node sensor network.

Transition flight of a concept of lifting-wing quadcopter

Abstract This paper presents the concept of a lifting-wing quadcopter unmanned aerial vehicle (UAV), a vertical take-off and landing vehicle (VTOL) with a rear wing, a canard at its front and four propellers. The aerodynamic surfaces are designed so that their mounting angle can be adjusted and fixed before flight, so its performance in transition flight can be studied for a combination of wing and canard mounting angles. A dynamic model using rigid-body equations of motion is presented, which is used to compute the transition flight trajectory from hover to cruise in horizontal flight. The trim conditions were computed for a range of fixed wing and canard mounting angles to study the effects of these variables on transition trajectory parameters such as required power, body pitch angle and propeller rotation speeds as a function of flight speed. Furthermore, a transition flight control algorithm is presented, which has a cascaded PID controller and a reference scheduler to switch between the proper reference states, controls and control allocation matrix. Finally, the transition control algorithm of the conceptual UAV is numerically simulated. Results show that this configuration can perform a fast and smooth transition from hover to cruise flight using the proposed flight control algorithm, substantially reducing required propulsive power in cruise of up to 64%. The application of the control algorithm made notable a transition manoeuver that consists of negatively inclining the aircraft at a negative pitch angle, initially at high intensity, and as the final cruising speed approaches, the inclination is attenuated until the equilibrium pitch angle is reached. Simultaneously with the negative inclination of the pitch angle, there is a slight drop in altitude, which is quickly resumed as the trajectory develops until the final cruising speed. Lastly, this aircraft configuration can be widely used in applications where performance gains in operations currently carried out by multicopters, which cover large distances and need long flight time, would bring great operational advantages.

Effects of Core and Surface Materials on the Flexural Behavior of Lightweight Composites Sandwich Beams

Sandwich composite elements are used in many sectors thanks to their low weight/strength ratios, high bending strength, good thermal insulation properties, and low costs. It is widely used in the machinery and construction industry, especially in land, sea, and air vehicles. The main objective of this research is to design and produce lightweight, durable, insulated, and low-cost, sustainable building elements that will meet emergency shelter needs after disasters. For housing purposes, 24 sandwich beams were prepared, eight designs with different surface coatings and core materials, and three in each design group. The effects of surface coating and core material on behavior were investigated with four-point bending experiments. Load-displacement relationships were determined from the experiments, and the beams' load-carrying capacities and failure patterns under the effects of bending and shearing were determined. In addition, theoretical methods determined maximum load values and compared them with the results of the experiments. As a result of the experiments, it was concluded that the best-performing design under bending effects was sandwich beams with plywood surface and XPS core.

YOLO-RWY: A Novel Runway Detection Model for Vision-Based Autonomous Landing of Fixed-Wing Unmanned Aerial Vehicles

In scenarios where global navigation satellite systems (GNSSs) and radio navigation systems are denied, vision-based autonomous landing (VAL) for fixed-wing unmanned aerial vehicles (UAVs) becomes essential. Accurate and real-time runway detection in VAL is vital for providing precise positional and orientational guidance. However, existing research faces significant challenges, including insufficient accuracy, inadequate real-time performance, poor robustness, and high susceptibility to disturbances. To address these challenges, this paper introduces a novel single-stage, anchor-free, and decoupled vision-based runway detection framework, referred to as YOLO-RWY. First, an enhanced data augmentation (EDA) module is incorporated to perform various augmentations, enriching image diversity, and introducing perturbations that improve generalization and safety. Second, a large separable kernel attention (LSKA) module is integrated into the backbone structure to provide a lightweight attention mechanism with a broad receptive field, enhancing feature representation. Third, the neck structure is reorganized as a bidirectional feature pyramid network (BiFPN) module with skip connections and attention allocation, enabling efficient multi-scale and across-stage feature fusion. Finally, the regression loss and task-aligned learning (TAL) assigner are optimized using efficient intersection over union (EIoU) to improve localization evaluation, resulting in faster and more accurate convergence. Comprehensive experiments demonstrate that YOLO-RWY achieves AP50:95 scores of 0.760, 0.611, and 0.413 on synthetic, real nominal, and real edge test sets of the landing approach runway detection (LARD) dataset, respectively. Deployment experiments on an edge device show that YOLO-RWY achieves an inference speed of 154.4 FPS under FP32 quantization with an image size of 640. The results indicate that the proposed YOLO-RWY model possesses strong generalization and real-time capabilities, enabling accurate runway detection in complex and challenging visual environments, and providing support for the onboard VAL systems of fixed-wing UAVs.

Noise and inflow velocity measurements of fixed pitch rotors in edgewise flight

A common design of many of the proposed generation of electric Vertical Takeoff and Landing (eVTOL) vehicles involves fixed pitch rotors in edgewise flight. These applications typically have significantly lower tip Mach numbers than conventional rotor-craft and involve distributed smaller rotors making them operate at lower Reynolds numbers and hence likely having a greater sensitivity to gusts and environmental turbulence. This work will present results of studies with fixed pitch rotors conducted in the UF Anechoic Wind Tunnel Facility. The studies involve radiated noise, thrust and stereoscopic Particle Image Velocimetry to measure the inflow velocity to the rotor plane. The measurements were taken for un-altered free stream conditions as well as ones subjected to three different turbulence generation grids. The results provided show that there can be effects at moderate levels of free stream to turbulence to the rotor efficiency and radiated noise.

Inclined Installation Effect on the Offset Strip Finned Heat Exchanger Designed for a Hybrid Electric Propulsion System in Electric Vertical Take-Off and Landing

The plate-fin heat exchanger was designed for the liquid cooling thermal management system of the hybrid electric propulsion system for an electric vertical take-off and landing (eVTOL) vehicle. The offset-strip fin design was applied, and the performance of the heat exchanger was evaluated, particularly with respect to the inclination of the airflow entering the heat exchanger. The estimated performance during the design phase matched well with the experimental results. The inclination of the heat exchanger had a minimal effect on thermal performance, with a slight increase in performance as the inclination increased. However, the pressure difference along the airflow was affected, likely increasing as the inclination increased. The sensitivity of various parameters on coolant temperature was also investigated. The air inlet temperature had a significant effect on coolant temperature, followed by the coolant flow rate. Therefore, when designing the thermal management system, careful consideration should be given to the ambient air temperature and coolant flow rate.

Incremental Sliding Mode Control for Predefined-Time Stability of a Fixed-Wing Electric Vertical Takeoff and Landing Vehicle Attitude Control System

Incremental Sliding Mode Control for Predefined-Time Stability of a Fixed-Wing Electric Vertical Takeoff and Landing Vehicle Attitude Control System

Review Research paper on Highly Energy Efficient Aerodynamic Shape for Flying Cars

The reviewed research paper presents an analysis of the aerodynamic design for flying cars, focusing on optimizing shape to achieve high energy efficiency. Given the increasing interest in urban air mobility (UAM) and eVTOL (electric vertical take-off and landing) vehicles, energy efficiency is critical for extending range, minimizing power consumption, and ensuring safe operations. The paper explores how specific aerodynamic principles can be applied to flying cars to minimize drag, reduce energy consumption, and enhance flight stability.

Enabling fast discharge of Li-ion batteries via electrolyte formulations for urban air mobility applications

High-power discharge requirements are critical for lithium-ion batteries (LIBs) used in electric Vertical Takeoff and Landing (eVTOL) vehicles that are increasingly considered in urban mobility. This investigation places a particular emphasis on understanding the impact of electrolytes on discharge processes and rate capability. We aim to compare the discharge behavior of LiBs using a conventional electrolyte (Gen 2: 1.2 M LiPF6 in EC:EMC) and the dual salt LiTFSI-LiBOB-based electrolyte. We carefully examine the profiles of charging and discharging, the behavior during extended cycles, impedance spectroscopy results, and the characteristics of the electrode surface. Our research findings demonstrate the complex relationship between the composition of electrolytes and the specific high-power discharge requirements of eVTOL systems. This research highlights the importance of customizing electrolyte compositions to optimize energy storage density while simultaneously enabling higher power extraction to enhance performance in short-range electric aviation.

Review Research Paper on Highly Energy Efficient Electric Drive for Flying Cars

The research paper presents an investigation into the design and optimization of a highly energy-efficient 3.5 kW electric drive for use in flying cars. As urban air mobility (UAM) and electric vertical take-off and landing (eVTOL) vehicles gain traction, the importance of energy-efficient electric propulsion systems becomes more prominent. The paper explores innovative approaches to achieving high energy efficiency, lightweight construction, and improved performance in electric drives for flying cars.

A New Data Fusion Method for GNSS/INS Integration Based on Weighted Multiple Criteria

The standard Kalman filter and most of its enhancements are typically designed based on the criterion that minimizes the mean squared error, with little discussion of multiple criteria in the positioning and navigation fields. Therefore, a novel data fusion method that takes into account weighted multiple criteria is proposed in this paper, implementing a filtering algorithm based on integrated criteria with different weights determined by a weight adjustment factor. The proposed algorithm and conventional filtering algorithms were utilized for data fusion in GNSS/INS integration. Experiments were conducted using actual data collected from an urban environment. Comparative analysis revealed that, when utilizing the proposed algorithm, the precision of the position, velocity, and attitude of the tested land vehicle could be improved by approximately 24%, 48%, and 35%, respectively. Furthermore, a series of filtering algorithms with different weight adjustment factors was performed to test their influence on the filtering. The application of the proposed algorithm should be accompanied by an appropriate weight adjustment factor.

Unmanned aerial vehicle landing localization technology based on visual dual-channel uniqueness coding

Unmanned aerial vehicle (UAV) mainly uses GPS (Global Positioning System) for positioning, but it is difficult to locate in areas where GPS signal is missing or being disturbed. Therefore, the relative positioning technology based on visual method is also widely used in UAV landing, but due to the influence of cross wind and the motion of the landing plane, the traditional visual landing sign and positioning method is prone to lose the positioning target at the end stage of the landing. Therefore, this article proposes a landing sign based on double-layer unique coding, which can realize continuous positioning in the horizontal direction and accurate positioning of large-scale changes in the vertical direction. Firstly, real-time image acquisition and image processing are carried out through the airborne camera. Based on the flight altitude and encoding extraction effect of the UAV, the red or blue channel component is extracted, and then the image is preprocessed, edge detection, line detection, coding grid extraction, etc. As long as any 5 × 5 small squares of the whole pattern can be extracted, the perspective-n-point algorithm is used to obtain the relative pose estimation between the UAV and the landing sign. Experiments show that the landing sign and recognition algorithm effectively improve the UAV landing reliability.

A Hybrid Algorithm of LSTM and Factor Graph for Improving Combined GNSS/INS Positioning Accuracy during GNSS Interruptions.

In urban road environments, global navigation satellite system (GNSS) signals may be interrupted due to occlusion by buildings and obstacles, resulting in reduced accuracy and discontinuity of combined GNSS/inertial navigation system (INS) positioning. Improving the accuracy and robustness of combined GNSS/INS positioning systems for land vehicles in the presence of GNSS interruptions is a challenging task. The main objective of this paper is to develop a method for predicting GNSS information during GNSS outages based on a long short-term memory (LSTM) neural network to assist in factor graph-based combined GNSS/INS localization, which can provide a reliable combined localization solution during GNSS signal outages. In an environment with good GNSS signals, a factor graph fusion algorithm is used for data fusion of the combined positioning system, and an LSTM neural network prediction model is trained, and model parameters are determined using the INS velocity, inertial measurement unit (IMU) output, and GNSS position incremental data. In an environment with interrupted GNSS signals, the LSTM model is used to predict the GNSS positional increments and generate the pseudo-GNSS information and the solved results of INS for combined localization. In order to verify the performance and effectiveness of the proposed method, we conducted real-world road test experiments on land vehicles installed with GNSS receivers and inertial sensors. The experimental results show that, compared with the traditional combined GNSS/INS factor graph localization method, the proposed method can provide more accurate and robust localization results even in environments with frequent GNSS signal loss.

An Experimental Study of Odometer as a Navigation aid for Land Vehicle Application

Strap-down inertial navigation system (SINS) shall provide position, velocity, and orientation information with reference to a pre-defined reference frame. The SINS shall have excellent accuracy over a short duration and is highly self-contained. However, the errors in navigation solutions build up exponentially with time and make the system output very unstable. In order to mitigate these errors, there is a need for a damping mechanism through external aiding sensors. In this article, one such approach is proposed to improve navigation accuracy for land vehicles in the GNSS (Global Navigation Satellite Systems) denied environment. The design and implementation of an odometer are carried out with the use of inductive proximity sensors and a mounting assembly to attach the odometer to one of the non-steering wheels of a vehicle. The odometer gives the pulse-high and pulse-low output with reference to the rotation of the wheel to which it is attached. Vehicle ground velocity is derived through sensed output pulses processed through quadrature decoder circuitry. Odometer measurements along with non-holonomic constraints (NHC) are used for minimizing velocity and position errors in SINS using an extended Kalman Filter (EKF) technique. Field trials are carried out to validate the proposed scheme of hybrid navigation with odometer design and experimental results are presented with a positioning accuracy of 0.05 % of distance travelled (DT).