Sustainability in Agricultural Mechanization: Assessment of a Combined Photovoltaic and Electric Multipurpose System for Farmers

This study is dedicated to the assessment of the possibility of replacing fossil fuels with renewable energy as a source of power in modern agriculture. We examined the use of a completely sustainable agricultural mechanization system based on a renewable energy system and a battery powered, multi-purpose agricultural vehicle. This assessment is based on the RAMseS project, financed by the European Commission under the 6th Framework Program, which has led to the actual manufacturing of the system, at present being tested in Lebanon. In the present study, we assess the environmental and economic performance of the RAMseS system. We evaluate the external costs by means of a specific model that takes into account the life-cycle cost (LCC), economical indexes, and life-cycle emissions for the vehicle during its life span. The results are compared with those of a standard vehicle based on the internal combustion engine (ICEV). The results show that the RAMseS system can avoid the emission of about 23 ton of CO2equ per year. The life cycle cost (LCC) assessment using MATLAB software shows that the LCC for the RAMseS vehicle and the ICEV are the same for a fuel unit price (pf) of 1.45 €/L. Finally, we show that almost 52 % of the RAMseS LCC is due to the batteries of the electric vehicle. A 50% decrease in batteries unit cost would cause the LCC of two system to be the same at a fuel cost of 0.8 €/L. The final result is that the RAMseS system remains—at present— marginally more expensive than an equivalent system based on conventional fuels and internal combustion engines. Nevertheless, with the gradual depletion of fossil fuels, all electric agricultural mechanized system provide an alternative solution that is dependent only on renewable energy and recyclable resources

Design, development, and evaluation of a PV_Bio-Gen range extender for an off-road electric vehicle

Transformation from fossil fuels to clean energy is necessary due to the stricter environmental protection policies. Drivetrain hybridization by green energy sources seems to be an appropriate solution in farm applications. However, some constraints are raised, e.g., the low energy density of renewable energy sources and the long recharging time of batteries. Hence, the objective of this work is to suggest an Extended-Range Solar Assist Plug-In Hybrid Electric Tractor (E-RSAPHT) via a combination of a photovoltaic (PV) system and a biogas fuelled engine generator set (Bio-Gen) with a battery pack. Due to multi-power sources, a heuristic control strategy is proposed to split the generated powers while considering the extend daily operation hours. Moreover, some field measurements are conducted to define typical working cycles for farm hybrid vehicle application. Considering these points, the modelling, simulation and development of the E-RSAPHT are presented in this paper. Experimental results showed that the proposed system could improve energy autonomy and fuel efficiency. For typically evaluated toolbars, the operation ranges of the trailer, boom-type sprayer, and water-pump system were extended up to 292, 255, and 320% compared to the base battery-electric tractor, respectively. The conducted investigations illustrate that even for a 2100kg electric farm vehicle, a downsized 4.4kW Bio-Gen allows the hybrid-electric system to supply the power demand compared to the conventional system by using the internal combustion engine

An intelligent energy management strategy for an off-road plug-in hybrid electric tractor based on farm operation recognition

Abstract Due to the growing emergence of vehicle electrification, agricultural tractor developers are launching hybrid powertrains in which energy management strategy (EMS) assumes a prominent role. This work mainly aims at developing an EMS for a plug-in hybrid electric tractor (PHET) to minimise fuel consumption and increase the operating range. The developed off-road PHET power sources are composed of a biogas-fuelled Internal Combustion Engine Generator (Bio-Gen), a photovoltaic system, and a battery pack. To control the power flow among different sources, a two-layer EMS is formulated. In this regard, initially, the farm operating mode is recognised by means of classification of a working cycle's features. Then, a control strategy based on a multi-mode fuzzy logic controller (MFLC) is employed to manage the power flow. At each sequence, the classifier identifies the farm operation condition and accordingly activates the relative mode of the MFLC to meet the requested power from the Bio-Gen. The performance of the proposed EMS has been evaluated based on three real-world typical agricultural working cycles. The results demonstrate the successful performance of the proposed intelligent EMS under farm conditions by maintaining the energy sources' operation in a high-efficiency zone which can lead to the extension of the working range and decrease fuel consumption

The treatment of printing and packaging wastewater by electrocoagulation– flotation: the simultaneous efficacy of critical parameters and economics

In this work, electrocoagulation–flotation (ECF) following sedimentation was applied as a printing and packaging wastewater treatment using four Al electrodes with a parallel monopolar configuration. A sedimentation process was applied after the ECF as a post-treatment phase to remove large pollutants. The simultaneous efficacy of the operating parameters initial color content (1,843.44–12,156.56 ADMI), initial pH (3.56–10.44), current density (6.02–22.18 mA/cm2), and treatment time (5.62–74.38 min) on color and chemical oxygen demand (COD) removal efficiencies were evaluated alongside processing costs. Response surface methodology (RSM) and central composite design (CCD) optimized these key parameters to achieve the highest removal efficiencies and lowest operating costs. Based on the results analyzed by RSM-CCD, using initial color content of 5,576.38 ADMI, initial pH of 7.29, the current density of 18.49 mA/cm2, and treatment time of 59.76 min as optimum operational conditions can result in 97.8% and 92.1% for color and COD removal efficiencies, respectively. At these optimum conditions, operating costs (OPCs), including electrodes material and energy consumption, were 0.07 US$/(kg color removed) and 0.4 US$/(kg COD removed). The results confirm ECF-sedimentation as a promising and costeffective tool for the treatment of printing and packaging wastewater

An operational scrutinization of autonomous tractor-trailer robot considering motion resistance force of rubber tracked undercarriage

In realm of researches involved in autonomous tractor-trailer robot, novel purpose of this research has been dedicated to motion resistance force of rubber tracked undercarriage of the robot. Hence, the motion resistance force was ascertained as affected by operational variables of robot forward speed (0.17, 0.33 and 0.5 m/s) and payload weight (1, 2, 3, 4 and 5 kN). Analytical results clarified that meaningful contribution of payload weight to the motion resistance force (15.26–28.05 N) was marginal (< 8 times) in comparison with that of robot forward speed. Hence, adjustment of the forward speed than payload weight is suggested as priority. Modeling results described that combinatorial effect of robot forward speed and payload weight on the motion resistance force was synergetic. This disclosed linear increasing dependency of the motion resistance force on concurrent proliferation of robot forward speed and payload weight. Overall, these results are profitable for redesign and performance optimization of tractor-trailer robot with rubber tracked undercarriage in order to proliferate autonomous transportation capacity of payloads, especially for indoor and outdoor shipping and warehouse of factories and industrial environments

Liveness Verification in TRSs Using Tree Automata and Termination Analysis

Contains fulltext : 83519.pdf (publisher's version ) (Open Access

Simulation, Development and Evaluation of an Autonomous Robotic Boat Used in Aquacultures

Introduction As the world population grows up, the quantity and quality of human food must be improved. The production yield of marine aquaculture and farming of aquatic organisms, as a valuable source of food, will be increased. Regular and online monitoring of the physical, chemical, and biological qualities of water and environmental parameters in such these controlled environments can be achieved by using advanced world technologies, such as autonomous boats. In this study, simulation of an autonomous boat has been done to help better understanding and control of this type of vessel in various environments such as dams, ports, rivers, aquatic ecosystems, and aquaculture. Hence, the main goal of this paper is to simulate and evaluate the guidance and navigation system of an autonomous boat based on the Fourth order of Runge-Kutta for determining the changes of water quality indices in a fish farming ponds. Materials and Methods In order to achieve the main goal of this study, an autonomous boat was designed and built. This boat as a general-purpose robotic trimaran boat has dimensions of 110 cm x 37 cm x40 cm and is made of Plexiglas 2 mm thick. Maximum forward speed of the boat is 125 cm s-1 (at 6850 rpm of brushless motors) and the turning radius is less than 61 cm. The environmental data can be transferred using Internet of Things (IOT), smartphones, SMS, and mini PC. The position and heading of the boat are determined using GPS and IMU data. The hydrodynamic and aerodynamic forces, moments, and coefficients of the boat model are determined and then applied in the mathematical simulation as the input of classic Runge-Kutta (RK4). The performance of the robotic boat navigational and control systems evaluated in a rectangular track with a length of 20 m and a width of 15 m in a fish farming pond in Karaj and 4 waypoints. The local coordinates of four corner of the mentioned rectangular in the pond was (0, 0), (0, 20), (15, 20), and (15, 0). The purpose of control system was to conduct the actuators in such way that boat be able to go to the next point. When the boat reaches the target distance of one m of the desired point, the next point will be introduced as a new target. The set point of boat speed was 0.4 m s-1 and zero state vector was [0, 0, 0, 0, 0, 0].  Results and Discussion The maximum error of position and heading of the autonomous boat is 135 cm and 11 degrees, respectively. Also, in the speed PID controller test (40 cm s-1), the average and standard deviation of the speed calculated as 40 cm s-1 and 2 cm s-1, respectively. Maximum difference between the heading obtained from the Kalman filter and received from the GPS is 11 degrees. In some situations that high precision of heading angle is not required, the GPS data can provide such accuracy of the heading. Among the variables of longitudinal, latitude, time to reach the target area, yaw rate, heading, and forward speed the minimum and maximum of percentage error are related to forward speed and yaw rate, respectively. These values show good performance of the simulated model and PID controllers. Conclusions In this study, motion simulation and evaluation of a robotic boat was carried out using a model boat and MATLAB software. The mathematical model simulated the real boat behavior correctly and the boat can be used safely in fish farming ponds to monitor environmental conditions and water quality