Stationary Vehicle Research Articles

Maneuverability and Movement Stability of Buses of the Especially Large Size Class

One of the main problems of modern big city is the global crisis of normal urban environment operation as a result of structural growing of automobilization level, oversaturation of road-street network by the transport streams. Buses of the especially large size class occupy, at the least, 20% in the structure of a modern bus park. The buses of especially large size classes, with the aim of necessary maneuverability, as a rule are made articulated.One of the ways of improving the maneuverability of articulated buses is the usage of guided towed sections. Solving the mentioned problem usually needs the mathematic models for predicting the vehicle behavior.The aim of introducing the trailer direction is to increase the overall traffic lane of an articulated bus that ensures a necessary maneuverability. The aim is gained by a choice of a rational transmitting ratio of trailer axle gear and necessary value of braking moment on one of its wheels.The solving of the problem concerning the stability of an articulated bus with a guided trailer axle was made by the way of analyzing the linear approaching of stationary vehicle movement.An influence of the construction parameters of the bus and the trailer, a transmitting ratio of control gear and a value of braking moment on the parameters of bus maneuverability were analyzed. It was proved that for an articulated bus, the normal maneuverability parameters can be ensured at the trailer direction by a way of braking of one of the wheels.

Abstract 18234: The Fast and the Furious, A Rare Case of RCA Dissection Following a Car Accident in a Male Patient

Introduction: Coronary artery dissection is a rare, but potentially lethal, etiology of chest pain in the emergency department. Dissection is defined as a spontaneous, traumatic, or iatrogenic disruption of the tunica intima, causing blood to accumulate in a false lumen. Coronary artery dissection reportedly has a 0.1% incidence in the general population, occurring most commonly in the LAD, and less commonly in the RCA. Acute myocardial infarction (AMI) following blunt chest trauma has an age predominance of 82% being less than 45 years of age. With a low incidence and abnormal age presentation, an electrocardiogram must be included in the work-up of blunt chest trauma to assess for coronary artery dissection. Case: A 44-year-old male with a history of polysubstance abuse, obesity, and hypertension presented with left hip pain following a motor vehicle accident. The patient had been operating a small motorcycle when he struck a stationary vehicle. He was wearing a helmet but was ejected from the motorcycle, landing on his back. The patient eventually began to experience both right-sided chest pain as well as right-sided neck pain while in the. An electrocardiogram was performed that showed inferior ST-segment elevation with reciprocal ST-segment depression in the lateral leads. Troponins were 42ng/L, 1,465ng/L and 8,170ng/L. Cardiac catheterization revealed a spiral dissection of the RCA extending from the ostium to the mid-segment with TIMI 1 flow. The patient remained on medical management of aspirin, clopidogrel, and heparin and was monitored in intensive care for 48 hours prior to home discharge. Conclusion: Blunt force cardiac injury is an uncommon cause of chest pain and myocardial infarction, and rarer still is RCA dissection. This case highlights the distinct importance of electrocardiograms as a pivotal part of the trauma and chest pain diagnostic reasoning process.

Handcrafted and Transfer Learned Feature Techniques for Vehicle Make and Model Recognition on Nigerian Road

The vehicle makes and model recognition (VMMR) is a challenging task due to the wide range of vehicle categories and similarities between different classes. Studies have shown that works have recognized vehicles of different countries' make and models. Popular vehicles on Nigerian roads may include products like; Toyota, Honda, Peugeot, Benz, Innoson Vehicle Manufacturing (IVM), etc. The VMMR is important in the intelligent transport system hence, this paper presents a handcrafted and transfer learning model to detect stationary vehicles and classify them based on brand, make, and model. A new dataset was introduced consisting of selected images of popular brands of vehicles driven on Nigerian roads. Framework for a vehicle make and model recognition was developed by extracting features using EfficientNet and HOG models and evaluated on the locally gathered datasets. For classification, a linear Support Machine Vector (SVM) was used. Experimental results showed 94.5% on HOG, 97% with EfficientNet, and 98.1% accuracy when HOG and EfficientNet features were concatenation. The proposed concatenated model outperformed HOG and EfficientNet extracted features by providing higher accuracy and confusion matrix with the highest number of classified images. The study shows the advantages of the proposed model in terms of its accuracy in terms of identifying the vehicle make and model.

Vehicle Detection and Attribution from a Multi-Sensor Dataset Using a Rule-Based Approach Combined with Data Fusion.

Vehicle detection using data fusion techniques from overhead platforms (RGB/MSI imagery and LiDAR point clouds) with vector and shape data can be a powerful tool in a variety of fields, including, but not limited to, national security, disaster relief efforts, and traffic monitoring. Knowing the location and number of vehicles in a given area can provide insight into the surrounding activities and patterns of life, as well as support decision-making processes. While researchers have developed many approaches to tackling this problem, few have exploited the multi-data approach with a classical technique. In this paper, a primarily LiDAR-based method supported by RGB/MSI imagery and road network shapefiles has been developed to detect stationary vehicles. The addition of imagery and road networks, when available, offers an improved classification of points from LiDAR data and helps to reduce false positives. Furthermore, detected vehicles can be assigned various 3D, relational, and spectral attributes, as well as height profiles. This method was evaluated on the Houston, TX dataset provided by the IEEE 2018 GRSS Data Fusion Contest, which includes 1476 ground truth vehicles from LiDAR data. On this dataset, the algorithm achieved a 92% precision and 92% recall. It was also evaluated on the Vaihingen, Germany dataset provided by ISPRS, as well as data simulated using an image generation model called DIRSIG. Some known limitations of the algorithm include false positives caused by low vegetation and the inability to detect vehicles (1) in extremely close proximity with high precision and (2) from low-density point clouds.

System modeling and temperature control for a fuel cell system based on local model networks

ABSTRACT Fuel cells have been studied for use in stationary power generation and vehicle propulsion systems. The fuel cell thermal management subsystem is coupled and nonlinear, posing challenges for modeling and temperature control. This paper aims to integrate the physical models of the fuel cell stack, pump, thermostat, and other components combined with intelligent algorithms into an efficient system-level thermal management model framework and develop a model predictive controller to solve the temperature control problem. First, a physics-based nonlinear model of the fuel cell system is developed and used as a basis to identify the linearized model for different operating points. Then, the global model is obtained by fusing the local models with Gaussian validity functions using the local linear model tree method. Third, a multi-step prediction model is derived based on the local model networks, and a parameterized linear state space form is obtained and used for controller design. Furthermore, an online correction method is developed to reduce the model discrepancy. Finally, the accuracy of the system model and the performance of the proposed controller are verified by open-loop experimental data and a series of closed-loop simulation cases.

Comparison of child and ATD belt fit and posture on belt-positioning boosters during self-selected, holding device, and nominal conditions

ObjectivePediatric anthropomorphic test devices (ATDs) are important tools for the assessment of child occupant protection and should represent realistic child belt fit and posture on belt-positioning boosters. Previous comparisons have been made to children in either self-selected or nominal postural conditions. This study compares belt fit and postural measurements between pediatric ATDs and a single cohort of children assuming different postures on boosters: self-selected, holding a portable electronic device, and nominal. MethodsA cohort of children (n = 25) were evaluated in a stationary vehicle on five boosters and in three postural conditions: nominal, self-selected, and a representative holding electronic device position. The Hybrid III 6- and 10-year-old and Q-Series 6- and 10-year-old ATDs were evaluated in the same five boosters and in two postural conditions: nominal and a representative holding electronic device position. A 3D coordinate measurement device was used to quantify belt fit (shoulder belt score, lap belt score, maximum gap size, and gap length) and anatomic landmark positions (head, suprasternale, ASIS, and patella). Landmark positions and belt fit were compared between ATDs and children for each booster and postural condition, and Pearson correlations (r) were assessed across boosters. ResultsATDs generally represented Nominal child postures across boosters. In the Device condition, ATDs were seldom able to be positioned to represent both the torso and head position of children, due to limited ATD spinal flexibility. When the torso position was matched, the ATD head was more rear by 63 mm. Correlations between Nominal child and ATD belt fit and belt gap metrics were generally weak and not significant, with the exception of lap belt score (all ATDs p < 0.07, r = 0.8549–0.9857). DiscussionATDs were generally able to represent realistic child postures and lap belt fit in Nominal and short duration Self-selected postures in a laboratory setting. However, these results display the potential difficulty of utilizing ATDs to represent more naturalistic child postures, especially the more forward head positions and flexed spinal posture associated with utilizing a portable electronic device.

The role of risk-based demand response in resource management of a grid-connected renewable-based large-scale microgrid with stationary and mobile energy storage systems and emission tax

Integration of energy storage systems with local electricity systems, like microgrids, is emerging due to their economical, reliability, and environmental benefits. These advantages can be achieved by load management subject to the related condition, such as the hour of the day, electricity price, etc. From an economic point of view, energy storage systems can reduce the share of costly power generators in supplying the peak demand. In other words, they can be charged in low-demand hours and discharged in peak-demand hours, when the electricity price is high. In this work, the impact of stationary battery storage and electric vehicles on the resource management of a large-scale microgrid is assessed through a stochastic model. The understudy microgrid includes also renewable energy sources (namely solar photovoltaic systems and wind turbines) as well as diesel generators. This study considers the uncertainty in the electricity price, where a scenario-based risk management approach is employed to control the risk associated with price uncertainty. The resulting model is implemented in the GAMS software package to be solved by a suitable solver. Numerical simulation of a large-scale microgrid is accomplished to validate the effectiveness of energy storage systems in the economic improvement of the understudy microgrid.

Developments in the cost of grid balancing services and the design of the European balancing market

Balancing services are traded on the balancing market, which has undergone major shifts in recent years due to external factors like the growing share of renewable energies in electricity production and the progressing electrification of society, especially in the mobility sector. This trend increases the demand for balancing services. However, market design is also changing to lower overall expenses for grid stability, which influences price volatility and overall costs for balancing services. Shorter provision times, low capacity limits, and a smaller gap between gate closure time and delivery time enable more flexible market participation of balancing service providers. This article provides an overview of the common European balancing market with a focus on Germany, including recent and upcoming regulatory changes and market design. Recent price trends highlight the importance of market design, especially provision times and price limits. The reduction of the provision time for Frequency Containment Reserve increased offered capacity per bid, and the end of the mixed price procedure in August 2019 led to a less concentrated price range for balancing energy. The introduction of the energy-only market in November 2020 shifted demand from tertiary to secondary control reserve. However, high energy prices in 2021 and 2022 have revealed the limited responsiveness of the balancing energy market. This effect will be reinforced with the exiting of coal-fired and nuclear plants from the pool of balancing service providers in the current decade. Additionally, the future development of the market depends on the integration of energy storage systems such as stationary batteries and electric vehicle batteries, including the regulatory framework.

Characteristics of automatic emergency braking responses in passenger vehicles evaluated in the IIHS front crash prevention program

Researchers can estimate the potential safety benefits of front crash prevention (FCP) systems by simulating system performance in rear-end crash scenarios reported to police or captured during naturalistic driving. Data to support assumptions about FCP systems in production vehicles, particularly automatic emergency braking (AEB), are limited. This study used detailed information from the Insurance Institute for Highway Safety’s (IIHS's) FCP evaluation to characterize interventions in vehicles that performed well (superior-rated vehicles) and those that did not perform as well (basic/advanced-rated vehicles) when approaching a stationary surrogate vehicle on a test track at 20 and 40 km/h, and estimated performance in similar conditions at higher speeds.Vehicle and video data from 3,231 IIHS FCP tests conducted at 20 and 40 km/h and 51 IIHS FCP research tests conducted at 50, 60, and 70 km/h with AEB responses were analyzed. Forward collision warning (FCW) and AEB time-to-collision (TTC), mean deceleration, maximum deceleration, and maximum jerk from the beginning of automatic braking to the end of braking or impact were computed for each test. Each dependent measure was modeled with test speed (20 km/h, 40 km/h), IIHS FCP test rating (superior, basic/advanced), and the interaction between test speed and rating. The models were used to estimate each dependent measure at 50, 60, and 70 km/h, and model predictions were compared with the observed performance of six vehicles in IIHS research test data.Vehicles with superior-rated systems warned and began braking earlier, had a greater average rate of deceleration, reached a higher peak deceleration, and had greater jerk than vehicles with basic/advanced-rated systems, on average. The interaction between test speed and vehicle rating was significant in each linear mixed-effects model, indicating that these differences changed with test speed. FCW and AEB in superior-rated vehicles occurred 0.05 and 0.10 s earlier, respectively, per 10-km/h increase in test speed compared with basic/advanced-rated vehicles. Mean deceleration and maximum deceleration for FCP systems in superior-rated vehicles increased 0.65 m/s2 and 0.60 m/s2 more, respectively, per 10-km/h increase in test speed than for systems in basic/advanced-rated vehicles. Maximum jerk increased 2.78 m/s3 per 10-km/h increase in test speed for basic/advanced-rated vehicles but decreased 0.25 m/s3 for systems in superior-rated vehicles. The root mean square error between the observed performance and estimated values at 50, 60, and 70 km/h indicated that the linear mixed-effects model had reasonable prediction accuracy for every measure except jerk at these out-of-sample data points.The findings from this study provide insight into the characteristics that make FCP effective for preventing crashes. Based on performance in the IIHS FCP test, vehicles with superior-rated FCP systems had earlier TTC thresholds and braked with greater deceleration that increased with speed compared with basic/advanced-rated systems. The linear mixed-effects models that were developed can guide assumptions about AEB response characteristics for superior-rated FCP systems in future simulation studies.

CFD simulations of a semi-transverse ventilation system in a long tunnel

In the present work, a semi-transverse ventilation system in a long tunnel with a length of 4.9 km, as a complex case study, is numerically studied by performing a set of three-dimensional steady incompressible computational fluid dynamics (CFD) simulations. The ventilation system consisted of a ceiling duct connected to two axial fans at the ending portals, and a series of jet fans in the main tunnel for supporting airflow in the desired direction. To focus on what can and cannot be achieved in commissioning tests, the ventilation system’s performance in various scenarios is numerically evaluated with two different tunnel states; empty tunnel and complete traffic congestion with 1176 stationary vehicles – which is almost impossible to evaluate during a commissioning test. By considering two hypothetical locations for the extraction zone from the main tunnel (in a distance of 450 and 1000 m from one portal), it is shown that the required number of jet fans in a traffic condition drops from 57 for the first extraction location to 43 (25% decrease) when the ventilation system extracts from the second zone. We show that if only the close axial fan to the extraction zone is activated, the required number of jet fans reduces by 56% and 72% for the first and second extraction locations, respectively. This finding can provide a cheaper and easier controlling scenario for emergency ventilation.

Theoretical and numerical investigation of bridge frequency identification employing an instrumented vehicle in stationary and moving states

In this study, theoretical and numerical means are used to investigate frequency identification of bridges using a vehicle in moving and stationary states. Unlike previous experimental studies, the current investigations provide theoretical and numerical understating of the stationary vehicle response due to the movement of another vehicle. First, the study introduces a novel closed-from solution of the dynamic responses of a vehicle in stationary state while the bridge is excited by another moving vehicle. The proposed equations are validated using a finite element (FE) model. Then, vehicle-to-bridge amplitude ratio is used to determine visibility of bridge frequency in the responses obtained by the closed-form solutions of moving and stationary vehicles. For an undamped and smooth surface conditions (assumptions used for the closed-from solution), the moving vehicle provided higher visibility of bridge frequency than that of the stationary vehicle parked at mid-span. To investigate the effects of damping and road roughness, numerical FE simulation is conducted. When the speed of the moving truck-trailer is 8 m/s and road roughness profile is of class A, 2nd and 3rd modes of bridge frequencies were not visible in the response of the moving vehicle, however; the stationary vehicle could detect all modes of frequencies up to the 3rd mode. For the first mode, although it was detected successfully by both moving and stationary vehicles, higher visibility of the stationary vehicle specially at quarter-span was always noticed. When lower speed of 2 m/s was used for the moving vehicle, 2nd and 3rd modes were identified successfully by both the moving and stationary vehicles, but with higher visibility in the stationary vehicle. However, when road roughness of class B was used, the moving vehicle again could not detect the 2nd and 3rd modes unlike the stationary vehicle.

Technological Support for Evaluation of Hydrogen Compatibility of Materials in Laboratory Conditions

Materials selection for hydrogen service is needed to support the deployment of hydrogen as a fuel as well as the development of codes and standards for stationary hydrogen use, hydrogen vehicles, refueling stations, and hydrogen transportation. Hydrogen energy infrastructure is currently in the process of development and in preparation for mass transportation of hydrogen gas and methane-hydrogen media involves significant use of the existing network of gas pipelines and formation of a network of hydrogen pipelines. Materials property measurement is needed on deformation, fracture and fatigue in hydrogen-containing media. Determination of steel properties such as strength, crack and fatigue resistance are priority to ensure safe design of pipelines transporting hydrogen gas or methane-hydrogen mixture. At the same time, there is a problem in technological support for evaluation of hydrogen compatibility of materials in laboratory conditions for evaluation of hydrogen embrittlement, depending on hydrogen concentration, methods and modes of loading, temperature, pressure and actual properties of materials.

The air exchange rate measuring method by the concentration of carbon dioxide in the vehicle cabin air

BACKGROUND: Vehicle passengers may be exposed to high concentrations of hazardous substances, especially in heavy traffic and traffic jams. The air exchange rate is an important factor in assessment of the level of pollutant substances exposure on the people inside the vehicle.&#x0D; AIMS: Development of the air exchange rate measuring method, based on carbon dioxide concentration build-up in the vehicle cabin air.&#x0D; MATERIALS AND METHODS: The presented method makes possible to determine the air exchange rate in a stationary vehicle or vehicle, moving with constant velocity. The set of experiments was carried out, in which the air exchange rate was determined in a stationary vehicle and in a moving vehicle at velocities of 30, 60 and 90 km/h. For each velocity, the air exchange rate was determined for three air conditioning system modes, such as intake air supply, recirculation mode and air conditioning system off.&#x0D; RESULTS: According to the results of measurements, the air exchange rate varied from 0.42 h-1 to 76.17 h-1.&#x0D; CONCLUSIONS: The study results corresponds to the results, obtained earlier by other authors, using alternative methods, and may be used for development of regulatory requirements to control the pollutant substances exposure on the people inside vehicle cabins and for the people healthcare strategy formation.

A Techno-Economic Assessment of a Second-Life Battery and Photovoltaics Hybrid Power Source for Sustainable Electric Vehicle Home Charging

This study discusses the use of a retired battery from an electric vehicle for stationary energy storage electric vehicle charging in a residential household. This research provides a novel in-depth examination of the processes that may be necessary to investigate the life loss of a battery, whether new or used. The main contribution is to promote the feasibility of the application from both a technical and economic point of view. The semi-empirical models are then utilized to analyze the life fading that is used in economic studies. In terms of lower initial investment costs for the battery and solar photovoltaics, the numerical calculation demonstrates that the used second-life battery with a DOD of 85% has more advantages over a new battery in the same condition. Additionally, compared to a new battery, a second-life battery gradually loses life and benefits from recycling after a projected 10-year lifespan. These results support the feasibility of the project. A discussion of project hurdles is included in which the hybrid converter modification may be achieved. Policymakers are encouraged to keep this valuable scheme in mind for the sake of margin profit and environmental preservation.

Deep learning for 6D pose estimation of objects — A case study for autonomous driving

Nowadays, the potential benefits and implementation of autonomous driving have attracted widespread attention from both industry and academia. This study will solve view-invariant object detection and semantic key-point pose assumptions from a single RGB image. A machine learning method for estimating the absolute pose of an on-road vehicle for autonomous driving from monocular vision alone without the help of additional sensors is a complex task. The main purpose of this work is to identify other vehicles on the road and estimate their exact angular position from a single image with improved accuracy. The focus of the study is to create a new algorithm by applying a potentially deep convoluted neural network followed by a repetitive neural structure for more accurate 6D pose inference. A 6D pose hypothesis is presented in this study, based on a deep hybrid architecture for individual vehicles of an end-to-end approach to a task consisting of a Convolutional Neural Network (CNN) and a Recurrent Neural Network (RNN). In this work, we will use a large-scale dataset consistent with the understanding of a 3D car instance called ApolloCar3D. The data set contains 5,277 real-life street scenes with examples of about 60K cars. By comparison, the ApolloCar3D is twenty times larger than the PASCAL3D+ and KITTI datasets. Ultimately, the idea is to efficiently eliminate motionless cars and predict the next pose given in the speed context, allowing a comprehensive evaluation, and passing the output through LSTM (long short-term memory) with an additional filter layer. The new filter added to the LSTM will efficiently filter and isolate stationary or parking vehicles and focus on on-road vehicles. Since the LSTM has a non-linear high-dimensional hidden memory state, it can preserve the past continuity of each generation’s data history and pay more attention to those road vehicles rather than parked or stationary vehicles to act accordingly. So for each new vehicle, the pose estimator classifier can use LSTM memory and compare the historical pose with the newly filtered data. The successful implementation of this innovative concept will lead to significant improvements in the real-life traffic situation in the field of computer vision and autonomous driving.

Vehicle Object Detection Based on Deep Learning

With the continuous improvement of science and technology and living standards, cars have become a necessary means of transportation for people to travel, which is bound to be followed by traffic accidents, so it is particularly necessary to detect or identify cars. Aiming at the above problems, this paper focuses on the application of deep learning in vehicle recognition problems, and is committed to finding a vehicle recognition algorithm with high recognition rate and stability. This paper focuses on the analysis of SSD algorithm and its basic theory convolutional neural network. Finally, this paper uses the pictures of stationary vehicles and a film video respectively to identify the stationary and moving state of vehicles. In the process of image recognition, the rationality and accuracy of the proposed method are verified according to the accuracy rate given above the image.

Confirmation of vehicle stability criteria through a combination of smoothed particle hydrodynamics and laboratory measurements

AbstractThis study combines laboratory experiments and numerical modelling in a novel manner to assess vehicle stability. Assessing vehicle stability forms the basis of hazard classification criteria, which in turn helps in forming safety guidelines for stream crossings and planning of evacuation routes in times of floods. These criteria are based on theoretical and physical model studies carried out on different vehicle models. This article demonstrates the application of a numerical method to determine the vehicle stability threshold so that the need for a physical model study for each kind of vehicle may be avoided. The numerical investigation is performed using smoothed particle hydrodynamics (SPH) with the vehicle oriented perpendicular to the flow direction, as this is the most critical orientation. A physical model study is also performed and its results are used to validate the SPH model. The results confirm the current Australian Rainfall and Runoff (ARR) safety criteria for stationary vehicles. It also suggests that the ARR stability curve can shift depending on the road conditions that affect the vehicle's sliding mechanism.

How Can the Trust-Change Direction be Measured and Identified During Takeover Transitions in Conditionally Automated Driving? Using Physiological Responses and Takeover-Related Factors.

This paper proposes an objective method to measure and identify trust-change directions during takeover transitions (TTs) in conditionally automated vehicles (AVs). Takeover requests (TORs) will be recurring events in conditionally automated driving that could undermine trust, and then lead to inappropriate reliance on conditionally AVs, such as misuse and disuse. 34 drivers engaged in the non-driving-related task were involved in a sequence of takeover events in a driving simulator. The relationships and effects between drivers' physiological responses, takeover-related factors, and trust-change directions during TTs were explored by the combination of an unsupervised learning algorithm and statistical analyses. Furthermore, different typical machine learning methods were applied to establish recognition models of trust-change directions during TTs based on takeover-related factors and physiological parameters. Combining the change values in the subjective trust rating and monitoring behavior before and after takeover can reliably measure trust-change directions during TTs. The statistical analysis results showed that physiological parameters (i.e., skin conductance and heart rate) during TTs are negatively linked with the trust-change directions. And drivers were more likely to increase trust during TTs when they were in longer TOR lead time, with more takeover frequencies, and dealing with the stationary vehicle scenario. More importantly, the F1-score of the random forest (RF) model is nearly 77.3%. The features investigated and the RF model developed can identify trust-change directions during TTs accurately. Those findings can provide additional support for developing trust monitoring systems to mitigate both drivers' overtrust and undertrust in conditionally AVs.

Mode Shape Identification and Damage Detection of Bridge by Movable Sensory System

Indirect method to identify dynamic properties of bridge by a passing vehicle is attractive recently since it does not require pre-installed sensors on bridge. However, the extracted dynamic properties are not accurate enough to identify local damages due to road surface roughness. To overcome this issue, a method to identify mode shapes and detect local damages in a simply supported bridge by movable sensory system is proposed in this study. Instead of using passing vehicles, two stationary vehicles are adopted in this study to perform as movable sensory system. They stay stationary at two different locations on the bridge subject to ambient environmental excitation, and their vertical accelerations are collected to calculate the vertical displacement of the two contact points between vehicles and bridge. Then they move to another two locations and the same procedures are repeated. After all locations along the bridge are tested, a matrix similar to frequency response matrix can be constructed and SVD method is used to extract the mode shapes. The element stiffness is thereafter evaluated by the fundamental mode shape, which can be then used to detect local stiffness reduction in the bridge. Numerical study has been conducted to validate the proposed method, and the effect of bridge damping, vehicle damping, measurement noise, and traffic flow is investigated. Moreover, field testing was conducted on Li-Zi-Wan Bridge and the results showed that the proposed method can re-construct the mode shapes and evaluate element bending stiffness as accurately as conventional direct approach. The proposed method is convenient and easy to implement in practice; and it is more robust because it is not affected by road surface roughness.

Solar power applications and integration of lithium iron phosphate batteries in off-grid photovoltaic system

Lithium iron phosphate battery is a type of rechargeable lithium battery that has lithium iron phosphate as the cathode material and graphitic carbon electrode with a metallic backing as the anode. It is a relatively new emerging energy storage battery that is Cobalt-free and Nickel-free. However, its integration with solar PV systems and the specific precautions for its use is not well known to most technicians and installers, especially in developing countries. In this paper, the issues on the applications and integration/compatibility of lithium iron phosphate batteries in off-grid solar photovoltaic systems are discussed. Also, the characteristics, properties, advantages, and disadvantages of the battery are presented. From the study, it is shown that if the battery operates with a charge control algorithm specially set for long charge durations, the energy storage system is an ideal choice for an off-grid photovoltaic system. This is due to their high energy density, long cycle life, relatively low cost compared to Li-ion, high safety, low toxicity, low risk of thermal runaway or combustion, low self-discharge rate, high capacity, lightweight, lower environmental impact, low maintenance, high cell voltage, fast charging, high-temperature stability, high discharge power, a good lifetime when deep cycled, etc. Additionally, the advantages have made the battery to be highly valued in energy storage, backup power, vehicle use utility-scale stationary applications, electric vehicles, commercial batteries , solar power, and other renewable energy applications, etc.