Land Vehicle Research Articles

On the prediction of noise generated by urban air mobility (UAM) vehicles. II. Implementation of the Farassat F1A formulation into a modern surface-vorticity panel solver

This study focuses on the integration of established acoustic prediction techniques directly into a surface-vorticity solver. The main objective is to enhance an aircraft designer's ability to characterize the acoustic signatures generated by urban air mobility (UAM) vehicles, in general, and distributed electric propulsion (DEP) concepts, in particular, including unmanned aerial vehicles. Our solver consists of a reliable, surface-vorticity panel code that incorporates viscous boundary-layer corrections. Thus, it offers a computationally efficient commercial tool for conceptual design and preliminary aerodynamic analysis. By implementing the Farassat F1A acoustics formulation directly into the solver, a new intuitive capability is achieved, which is both conversive with modern engineering tools and efficient in setup and speed of execution. In addition to its application to the X-57 high-lift propeller and the Revolutionary Vertical Lift Technology Tiltwing electric Vertical Take-Off and Landing (eVTOL) vehicle by the National Aeronautics and Space Administration, this capability is systematically demonstrated using three particular case studies. These consist of both single- and six-propeller Joby S4 eVTOL as well as a small eight-propeller Kittyhawk KH-H1 DEP vehicle. Although the details of this tool and underlying equations are showcased in this article, the acoustic metrics that can be effectively used to characterize the noise level generated by a UAM in flight are described in a companion article. By embedding this assortment of insightful metrics into a simple and user-friendly flow solver, a much improved flow-acoustic analysis capability is thereby provided to support the design of future aircraft.

Q-Rényi Kernel Functioned Kalman Filter for Land Vehicle Navigation

In this brief, a q-Rényi kernel functioned Kalman filter (qRKFKF) is proposed based on the q-Rényi kernel function which is to provide better flexibility and performance in non-Gaussian environment. The concrete realization of the proposed qRKFKF are created and analyzed in detail, and its performance is presented and discussed. Three examples are carried out to verify the performance of the proposed qRKFKF for land vehicle navigation via numerical simulations: large outliers in non-Gaussian noise, alpha-stable noise and diverse noise distributions that combines Gaussian and Laplace noises. Compared with Kalman filter (KF), Maximum Correntropy Kalman Filter (MCKF) and minimum error entropy KF (MEE-KF), the qRKFKF is superior to others for combating non-Gaussian noises.

A New Robust Filtering Method of GNSS/MINS Integrated System for Land Vehicle Navigation

Combining a global navigation satellite system (GNSS) and microelectromechanical technology-based inertial system (MINS) has become essential in land vehicle navigation systems. In an urban environment, the error of position output by GNSS receiver increases because of the blocking and reflection of the signal by buildings, which affects the positioning accuracy of the integrated system. In order to improve the positioning accuracy under these scenarios, this paper proposed a new robust method based on the estimation of the standard deviation of GNSS positioning error. In our study, a method for estimating the standard deviation <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">${\boldsymbol{\sigma}}^p$</tex-math></inline-formula> (or variance) of the position error of GNSS receiver is firstly proposed. Then a robust filtering method combined multi-factor scaling and bias estimation is proposed based on the estimation of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">${\boldsymbol{\sigma}}^p$</tex-math></inline-formula> . The simulations and vehicle navigation test show that the proposed method has a robust positioning effect. When <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">${\boldsymbol{\sigma}}^p$</tex-math></inline-formula> increases, the position accuracy is closed to the Sage-Husa filtering method with boundary constraint (SH-KF). Simulations also indicate that the proposed method has better robust effect than the traditional Kalman filter and SH-KF when a large bias error of position exists.

Multi-Scenario Trajectory Optimization for Vertical Takeoff and Vertical Landing Vehicles Using the Gauss Pseudospectral Method

Vertical takeoff and vertical landing (VTVL) vehicles, based on throttling liquid rocket engines, are attracting increasing attention for their validation of guidance and control techniques during landing. However, validation requires the vehicle to fly in a special trajectory with multiple constraints. Propellant consumption should be carefully calculated for the purpose of carrying more experimental devices during the flight, which makes conducting minimum-propellant trajectory optimization a necessity. This study focuses on the optimization of VTVL vehicles based on a throttling liquid rocket engine. Three flight scenarios applicable to this vehicle are proposed, namely, VTVL vehicles without horizontal movement, VTVL vehicles with horizontal movement, and vertical takeoff and autonomous landing with horizontal movement. Trajectory optimization using the Gauss pseudospectral method (GPM) was conducted during the abovementioned flight scenarios. The results show that the GPM provides excellent solutions for trajectory optimization in the different scenarios. In VTVL vehicles with horizontal movement, vertical takeoff, and autonomous landing with horizontal movement scenarios, the thrust appears in a similar bang–bang control. Meanwhile, in VTVL vehicles without a horizontal movement scenario, the thrust appears like a segmented bang–bang control, which we call regulative bang–bang control. Moreover, by introducing the thrust derivative into the optimization objective using a weighted method, thrust fluctuation can be restrained. To ensure the compatibility of switching the flight among the three scenarios, the carried propellant mass should be decided based on the third flight scenario.

Computational Investigation of Blade–Vortex Interaction of Coaxial Rotors for eVTOL Vehicles

In the design of electric vertical takeoff and landing (eVTOL) vehicles, coaxial rotors have garnered significant attention due to their superior space usage and aerodynamic efficiency compared to standard rotors. However, it is challenging to study the flow field near the rotors due to the blade–vortex interface (BVI) and vortex–vortex contact between two rotors. Using sliding mesh technology and Reynolds-averaged Navier–Stokes (RANS) solvers, a numerical method was established to simulate the flow field of a coaxial rotor in hover, which was verified by experiments. Using this method, this paper analyzes the relationship between position and intensity of the tip vortex of the upper rotor, the axial velocity of induced flow and the load distribution on the blades at the azimuth when the BVI phenomenon occurs with a difference in rotational speed and rotor spacing. The results indicate that, when the BVI phenomenon appears, the blade-tip vortex of the top rotor rapidly dissipates, and the load distribution of the lower blade changes due to the induced flow of the vortex. When the rotational speed increases, the spanwise thrust coefficient of each rotor changes slightly. The vortex–vortex interaction becomes stronger, which leads to vortex pairing. When the distance between the rotors decreases, the BVI phenomenon occurs at an earlier azimuth and the location of the BVI moves towards the tip of the lower blade. The vortex–vortex interaction is also enhanced, which leads to vortex pairing and vortex merging.

Visual Navigation Algorithm for Night Landing of Fixed-Wing Unmanned Aerial Vehicle

In the recent years, visual navigation has been considered an effective mechanism for achieving an autonomous landing of Unmanned Aerial Vehicles (UAVs). Nevertheless, with the limitations of visual cameras, the effectiveness of visual algorithms is significantly limited by lighting conditions. Therefore, a novel vision-based autonomous landing navigation scheme is proposed for night-time autonomous landing of fixed-wing UAV. Firstly, due to the difficulty of detecting the runway caused by the low-light image, a strategy of visible and infrared image fusion is adopted. The objective functions of the fused and visible image, and the fused and infrared image, are established. Then, the fusion problem is transformed into the optimal situation of the objective function, and the optimal solution is realized by gradient descent schemes to obtain the fused image. Secondly, to improve the performance of detecting the runway from the enhanced image, a runway detection algorithm based on an improved Faster region-based convolutional neural network (Faster R-CNN) is proposed. The runway ground-truth box of the dataset is statistically analyzed, and the size and number of anchors in line with the runway detection background are redesigned based on the analysis results. Finally, a relative attitude and position estimation method for the UAV with respect to the landing runway is proposed. New coordinate reference systems are established, six landing parameters, such as three attitude and three positions, are further calculated by Orthogonal Iteration (OI). Simulation results reveal that the proposed algorithm can achieve 1.85% improvement of AP on runway detection, and the reprojection error of rotation and translation for pose estimation are 0.675∘ and 0.581%, respectively.

Reinforcement learning based power management integrating economic rotational speed of turboshaft engine and safety constraints of battery for hybrid electric power system

Hybrid electric power system (HEPS) with turboshaft engine is a promising solution for the land and air vehicle, and the power management strategy (PMS) is the key to obtaining better performance of HEPS. In this paper, a reinforcement learning (RL)-based PMS integrating economic rotational speed (ERS) of turboshaft engine and safety constraints-based variable action space (SC-VAS) approach is proposed. First, an efficient algorithm based on the turbine performance map for calculating ERS is proposed, with low complexity which is 5.5% of the conventional algorithm. Second, based on the ERS feature, the SC-VAS approach is presented to further optimize the action space to prevent the discharging/charging power and state of charge of the battery from violating the safety constraints. Comparison results show that with no violation of constraints of battery, the convergence speed of RL agent incorporating the SC-VAS approach increases by 5 times, and the size of the optimized Q table decreases to 21.9% of that of the basic Q table. The proposed PMS with the ERS feature and SC-VAS approach can bring a 4.29% reduction in the fuel consumption under an air-land driving condition. Moreover, the results of the hardware-in-the-loop experiment demonstrate the real-time performance of the proposed strategy.

The concept of winged space vehicle marine horizontal landing by docking with ekranoplane

The article makes an overview of possible new means of space payload launching and landing. The possibilities of essential reducing the unit cost of space transportation are described. Both vertical and horizontal versions of the take-off and landing are allowed launching and landing vehicles of different configurations are analyzed by ensuring the reusable application of all elements of the space system, and not just the first stage of the launch vehicle. The advantages of using water areas for space needs are discussed. The opportunities and difficulties of application a heavy ekranoplane (WIG-craft) to assist the marine take-off and landing of an aerospace plane are explained. The flight safety requirements for maneuvering of both these winged vehicles for their reliable approach and docking are analyzed.

Performance analysis and dynamic optimization of integrated cooling and power generation system based on supercritical CO2 cycle for turbine-based combined cycle engine

Turbine-based combined cycle (TBCC) engines are the most promising propulsion systems for the horizontal takeoff and landing of hypersonic vehicles. However, the high air-inlet temperature, engine-wall temperature, and electrical-energy demand hinder the application of the system. In this study, a novel integrated cooling and power generation system based on a supercritical CO2 recuperative Brayton cycle for hypersonic vehicles was proposed to meet the cooling requirements of each operating stage of a TBCC engine and to provide continuous power. Several optimization parameters able to balance the characteristics of the limited cold source, system weight, and power output of the system, such as the power-to-weight ratio and heat sink saving ratio, were proposed. With the help of optimization algorithms, the global performance curves and loads of each component were obtained during flights in the range of Mach 3.2∼6. The recuperator heat duty and compressor inlet temperature were key design parameters that affected system performance. The compressor inlet temperature is known to alter the heat sink utilization by changing the pinch point location in the gas cooler. The recuperator heat duty impacted both the system weight and power generation. The dynamic performance of the system indicated that the minimum heat sink saving ratio was approximately 10% during the entire flight, implying that the volume of fuel carried by the hypersonic vehicle could be reduced to some extent, while sufficient electricity was generated. The proposed system is a novel solution for thermal protection of TBCC engines and aircraft power generation technology under limited cold-source conditions.

LTI-SAM: Lidar-Template Matching-Inertial Odometry via Smoothing and Mapping

Robust localization is an essential requirement for autonomous land vehicles. In similar scenes such as corridors and tunnels or open scenes such as airports and mines, the performance of the traditional algorithm of laser odometry will be seriously deteriorated or even become completely invalid due to the similarity of observation data. Based on the LIO-SAM algorithm, LTI-SAM is proposed in this article, that is to use the downward-facing camera and inertial measurement unit (IMU) to perform dead reckoning through template matching algorithm and use template matching visual odometry (VO) to judge themotion state and decidewhether to save the keyframe if the laser odometer fails and the keyframe is not saved. If the keyframe is kept, theVOis added between two keyframes instead of the laser odometry to optimize through the factor graph, which improves the accuracy of localization and mapping. The proposed algorithm with loose coupling between template matching VO and laser inertial navigation is implemented under the robot operating system (ROS) platform, and the algorithm is verified by indoor and outdoor experiments. Experimental results show that the proposed algorithm can bring significant performance improvement in both similar indoor scenes and outdoor degraded scenes.

Aerodynamic Characteristics of a Ducted Fan Hovering and Transition in Ground Effect

Ducted fans installed on vertical takeoff and landing vehicles experience significant ground effect during takeoff and landing. The aerodynamic characteristics of a ducted fan hovering and transitioning in the ground effect are studied using numerical simulations in this paper. The flowfields are obtained by solving Reynolds Averaged Navier–Stokes equations with the Multiple Reference Frame approach. When a ducted fan hovers in the ground effect, the blade thrust increases due to the combined effect of the increase in the effective angle of attack of the blade and the increase in ambient pressure; the duct thrust decreases due to the combined effect of the decrease in the effective angle of attack of the duct and the increase in ambient pressure. Stall occurs at a certain advance ratio and angle of attack when transitioning in the ground effect. The ground effect delays the occurrence of stall at some advance ratios. The ground effect is hardly detectable at angles of attack less than 30° even if the height drops to 0.5 times the duct exit diameter. At this height and high angles of attack, the different positions and influence regions of the ground vortex at different advance ratios contribute to the different variation trends in the ducted fan performance.

Deep Learning Approach for Unmanned Aerial Vehicle Landing

It is one of the biggest challenges to land an unmanned aerial vehicle (UAV). Landing it by making its own decisions is almost impossible even if progress has been made in developing deep learning algorithms, which are doing a great job in the Artificial Intelligence sector. But these algorithms require a large amount of data to get optimum results. For a Type-I civilization collecting data while landing UAV on another planet is not feasible. But there is one hack all the required data can be collected by creating a simulation that is cost-effective, time-saving, and safe too. This is a small step toward making an Intelligent UAV that can make its own decisions while landing on a surface other than Earth's surface. Therefore, the simulation has been created inside gaming engine from which the required training data can be collected. And by using that training data, deep neural networks are trained. Also deployed those trained models into the simulation and checked their performance

Biomimetic Super “Silicate” Phobicity and Superhydrophobicity of Ceramic Material

AbstractPlants exhibit a huge variety of biologically functional surfaces with rather unique characteristics. Analysis and mimicking of the surface leaf of the lotus plant have recently been used to develop biomimetic water repellency surfaces. A functional ceramic coating with the “lotus leaf effect” is also an interesting option in aggressive environments to mitigate corrosion by natural silicate melts. Here, inspired by natural superhydrophobic surfaces, and through the application of femtosecond laser pulses, a ceramic surface is fabricated with a hierarchical nano/microstructure. This ceramic surface exhibits the combined effects of super “silicate” phobicity at high temperature and superhydrophobicity at room temperature. The capability of the laser‐irradiated TBC is attributed to resist wetting by both silicate melt and water to its lotus‐leaf‐like dual‐scale microstructure, emulating in particular the existence of nanoparticles. These findings may be an important step toward next‐generation jet engines with greatly reduced vulnerability to environmental siliceous debris and mitigate lunar or Mars regolith dust sticking to the landing vehicle in the rocket engine exhaust plume and anti‐slagging in coal‐fired power plants or further industries.

A Linear-Active-Disturbance-Rejection-Based Vertical Takeoff and Acceleration Strategy with Simplified Vehicle Operations for Electric Vertical Takeoff and Landing Vehicles

A practical vertical takeoff and acceleration strategy is developed for manned electric vertical takeoff and landing vehicles, with a simple vehicle operation principle defined. Firstly, a 6-DOF model is established for 120 kg reduced-scale protype electric vertical takeoff and landing vehicles, with its physical control principles illustrated. Then, a simple vehicle operation method is defined for the vehicle, where the conventional operation method for fixed-wings and helicopters is considered for a friendly stick response definition for pilots with different backgrounds. The defined simple vehicle operation principles are realized by a control architecture with a linear-active-disturbance-rejection-control-based inner loop stability augmentation system and an airspeed-based mode selection outer loop. This system is then used to perform a four-stage vertical takeoff and acceleration strategy, which targets at a smooth and safe transition. The Monte Carlo simulation results and the strategy simulations prove that the proposed strategy, which achieves the design target perfectly, can be easily performed with the developed simple vehicle operation system, and that it has sufficient robustness performance to reject at least 20% of the model’s uncertainties.

Deep Reinforcement Learning with Corrective Feedback for Autonomous UAV Landing on a Mobile Platform

Autonomous Unmanned Aerial Vehicle (UAV) landing remains a challenge in uncertain environments, e.g., landing on a mobile ground platform such as an Unmanned Ground Vehicle (UGV) without knowing its motion dynamics. A traditional PID (Proportional, Integral, Derivative) controller is a choice for the UAV landing task, but it suffers the problem of manual parameter tuning, which becomes intractable if the initial landing condition changes or the mobile platform keeps moving. In this paper, we design a novel learning-based controller that integrates a standard PID module with a deep reinforcement learning module, which can automatically optimize the PID parameters for velocity control. In addition, corrective feedback based on heuristics of parameter tuning can speed up the learning process compared with traditional DRL algorithms that are typically time-consuming. In addition, the learned policy makes the UAV landing smooth and fast by allowing the UAV to adjust its speed adaptively according to the dynamics of the environment. We demonstrate the effectiveness of the proposed algorithm in a variety of quadrotor UAV landing tasks with both static and dynamic environmental settings.

Effects of Groove Structure on Spray Characteristics of a Throttleable Pintle Injector

Throttleable rocket engines are used for various purposes, including vertical landing of launch vehicles and soft landing on the surface of celestial bodies. The use of a throttleable pintle injector is a representative throttling method because of its ability to maintain the spray characteristics under different throttling levels. However, previous studies have reported changes in the spray characteristics of gas–liquid pintle injectors with varying throttling levels. To address this issue, a pintle tip with groove structure was developed in this study. Cold flow experiments were performed using normal and grooved pintle tips for a gas–liquid pintle injector, and the spray angle and average droplet size of the pintle injector were measured and compared. By changing the momentum and structure of the radial flow with added grooves, the spray angle increased and the droplet size decreased. The results indicate that adopting a grooved pintle tip can improve the spray characteristics of a pintle injector in terms of its correlation with combustion performance, particularly at low throttling levels. Additionally, a grooved pintle tip reduces the changes in spray characteristics under varying throttling levels, which is advantageous from the perspective of design simplicity.

THE PHENOMENON OF ADDITIONAL LEAF SPRINGS ON GOODS TRANSPORTATION VEHICLES (TRUCKS) REVIEWING FROM OVERLOADING AND VEHICLE SPEED FACTORS

The truck is land transportation that functions as effective transportation of goods in facilitating the goods distribution to all regions in Indonesia. In addition, roads play an important role as supporting infrastructure which is very important in facilitating these transportation facilities and other land vehicles. The increase in the number of leaf springs in vehicles is currently a common phenomenon among owners of goods/truck transport vehicles. The addition of leaf springs is intended so that the vehicle can carry an excess amount of goods (overload). This study aimed to find out how much overload each additional sheet of spring on the overload factor (excess load) which can trigger road damage and slow vehicle speed which can lead to traffic jams. The results on road damage research in general are the result of deflections and cracks due to excessive axle pressure and decreased vehicle speed with overload loads which cause long queues of vehicles in certain spaces and decreased ability of overloaded vehicles to climb. Control measures need to be taken for goods vehicles that increase the number of leaf springs because the addition of leaf springs allows goods transport vehicles to be overloaded which causes excessive pressure so that it is not in accordance with government regulations.

Environmental impact analysis of on-demand urban air mobility: A case study of the Tampa Bay Area

Urban Air Mobility (UAM) uses electric vertical take-off and landing (eVTOL) vehicles to provide an alternative way of transporting passengers in urban areas. This study proposes a method of comparing air pollutant emissions from using ground transportation versus switching to multimodal UAM, including greenhouse gases and other air pollutants (NO x , SO 2 , PM 2.5 ). A study by Wu and Zhang (2021) addressed planning questions regarding the optimal placement of vertiports and estimated diverted demand from ground transportation modes by combining network design and travel mode choice models. The proposed method is applied to the case study of Tampa Bay region. A sensitivity analysis was conducted to further evaluate the impacts. The study reveals that on-demand UAM (considering vertiport access and egress modes) generates more greenhouse gases and other air pollutants (except NO x ) in the case study region compared to ground transportation modes. The emissions depend on the structure of power production. A lower UAM service price and more vertiports will further increase emissions.

Land Vehicle Navigation Using Low-Cost Integrated Smartphone GNSS Mems and Map Matching Technique

Abstract The demand for smartphone positioning has grown rapidly due to increased positioning accuracy applications, such as land vehicle navigation systems used for vehicle tracking, emergency assistance, and intelligent transportation systems. The integration between navigation systems is necessary to maintain a reliable solution. High-end inertial sensors are not preferred due to their high cost. Smartphone microelectromechanical systems (MEMS) are attractive due to their small size and low cost; however, they suffer from long-term drift, which highlights the need for additional aiding solutions using road network that can perform efficiently for longer periods. In this research, the performance of the Xiaomi MI 8 smartphone’s single-frequency precise point positioning was tested in kinematic mode using the between-satellite single-difference (BSSD) technique. A Kalman filter algorithm was used to integrate BSSD and inertial navigation system (INS)-based smartphone MEMS. Map matching technique was proposed to assist navigation systems in global navigation satellite system (GNSS)-denied environments, based on the integration of BSSD–INS and road network models applying hidden Marcov model and Viterbi algorithm. The results showed that BSSD–INS–map performed consistently better than BSSD solution and BSSD–INS integration, irrespective of whether simulated outages were added or not. The root mean square error (RMSE) values for 2D horizontal position accuracy when applying BSSD–INS–map integration improved by 29% and 22%, compared to BSSD and BSSD–INS navigation solutions, respectively, with no simulated outages added. The overall average improvement of proposed BSSD–INS–map integration was 91%, 96%, and 98% in 2D horizontal positioning accuracy, compared to BSSD–INS algorithm for six GNSS simulated signal outages with duration of 10, 20, and 30 s, respectively.

FUTURE AIR TRANSPORTATION RAMIFICATION: URBAN AIR MOBILITY (UAM) CONCEPT: URBAN AIR MOBILITY

Urban Air Mobility (UAM) is a new concept offered for solving urban transportation system problems, contributing to reducing traffic congestion, atmospheric pollution and mobility around metropolitan areas which is progressively an evolved aviation market. Facing the evolved dynamics in the airspace and on the ground, developed new technologies are able to withstand against destroy transportation infrastructures of the big cities, making it necessary to develop UAM services in the megapolises and regional transportation sector. Based on new technologies and modern business approaches, applying the next generation aviation infrastructure makes it capable of setting up a novel air traffic within the urban environment. This case study aims to explore the urban air transport advantages, particularly adoption of UAM, which might be an alternative next generation air transportation system. Referring to the collected operational data and design performances of the UAM, in this paper, we will try to describe a multi approach studying differences between traditional aviation transportation and UAM operation. The first step of the study consists of defining an airspace classification for UAM mission and use of applicable requirements for air navigation service providers and second part of the study describes performing UAM infrastructure and design of vertiports necessary for vertical take-off and landing (VTOL) vehicles. Detailed design specification is not included in this study but limited characteristics are indicated according to the VTOL manufacturer that are obtained from the test results. As far as VTOL vehicles have not started their mission yet, the UAM operators are at the stage of development to set up their future operation. The expected trend provides justifiable assumptions of the necessity of establishing the new transportation ramification within the aviation industry, upon transforming existing business activities and regulations.