Energy Optimization by Parameter Matching for a Truck-mounted Concrete Pump
TL;DR: In this paper, a global power matching method is proposed based on both fuel consume rate of the engine and efficiency of the hydraulic pump, which is realized by genetic algorithm for low efficiency and large fuel consume of a truck-mounted concrete pump.
About: This article is published in Energy Procedia.The article was published on 2016-06-01 and is currently open access. It has received 5 citations till now. The article focuses on the topics: Hydraulic pump & Concrete pump.
Citations
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03 Nov 2019
TL;DR: This paper proposes to predict the fine-grained fuel consumption rate of each engine speed and torque combination, by learning a model from the incomplete and inconsistent observation data, and designs a novel FuelNet based on Convolutional Neural Networks and Generative Adversarial Networks.
Abstract: The high costs and pollutant emissions of vehicles have raised the demand for reducing fuel consumption globally. The idea is to improve the operations of vehicles without losing the output power such that the engine speed and torque work with the minimum fuel consumption rate. It relies on the complete map of engine speed and torque to fuel consumption rate, known as the engine universal characteristic map. Unfortunately, such a map is often incomplete (fuel consumption rate not observed under most engine speed and torque combinations) and inconsistent (different fuel consumption rates observed under the same engine speed and torque combination). In this paper, we propose to predict the fine-grained fuel consumption rate of each engine speed and torque combination, by learning a model from the incomplete and inconsistent observation data. A novel FuelNet is designed based on Convolutional Neural Networks (CNNs) and Generative Adversarial Networks (GANs). Deconvolution is employed to predict the incomplete fuel consumption rates, while the discriminator can successfully tolerate the inconsistent fuel consumption rate observations. Experiments show that our FuelNet outperforms the existing approaches in both imputing the incomplete and repairing the inconsistent fuel consumption rates. Remarkably, we deploy the predicted fine-grained fuel consumption rates in a mobile application to assist driving, and show that the fuel consumption can be reduced up to 12.8%.
10 citations
Cites background from "Energy Optimization by Parameter Ma..."
...Figure 3: Example of fuel consumption map [13], where red star denotes the point with the minimum fuel consumption rate under the same output power 60kW...
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TL;DR: In this article , the authors summarized the principles, concepts, and operation modes of electro-hydraulic hybrid power systems and provided a comprehensive analysis, comparison, and discussion of EHHV multi-mode working conditions in passenger vehicles, commercial vehicles and engineering machinery.
3 citations
14 Aug 2022
TL;DR: Experiments over real world datasets, including the aforesaid engine data collected by a vehicle manufacturer, demonstrate that the proposed bridge between tuple alignment and regression outperforms the existing methods on alignment accuracy and improves regression precision.
Abstract: Regression models are learned over multiple variables, e.g., using engine torque and speed to predict its fuel consumption. In practice, the values of these variables are often collected separately, e.g., by different sensors in a vehicle, and need to be aligned first in a tuple before learning. Unfortunately, flowing to various issues like network delays, values generated at the same time could be recorded with different timestamps, making the alignment diffcult. According to our study in a vehicle manufacturer, engine torque, speed and fuel consumption values are mostly not recorded with the same timestamps. Aligning tuples by simply concatenating values of variables with equal timestamps leads to limited data for learning regression model. To deal with timestamp variations, existing time series matching techniques rely on the similarity of values and timestamps, which unfortunately are very likely to be absent among the variables in regression (no similarity between engine torque and speed values). In this sense, we propose to bridge tuple alignment and regression. Rather than similar values and timestamps, we align the values of different variables in a tuple that (i) are recorded in a short period, i.e., time constraint, and more importantly (ii) coincide well with the regression model, known as model constraint. Our theoretical and technical contributions include (1) formulating the problem of tuple alignment with time and model constraints, (2) proving NP-completeness of the problem, (3) devising an approximation algorithm with performance guarantee, and (4) proposing efficient pruning strategies for the algorithm. Experiments over real world datasets, including the aforesaid engine data collected by a vehicle manufacturer, demonstrate that our proposal outperforms the existing methods on alignment accuracy and improves regression precision.
1 citations
TL;DR: In this paper , a review on energy conservation of construction machinery for pumping concrete is carried out, which comprises a quantitative analysis method and literature investigation method, where the structure and working principle of constructing machinery for concrete are expounded, and energy consumption ways of constructing concrete are analyzed.
Abstract: The excessive consumption of fossil fuel, energy shortage and global warming along with environmental deterioration have increasingly become a global issue. In order to deal with the energy crisis, energy conservation has been developed and applied in vehicles and construction machineries, i.e., excavators, loaders and forklifts. Due to the shortcoming of low efficiency, high-energy consumption and bad exhaust, the energy conservation of construction machinery for pumping concrete is necessary and urgent. This paper aims to carry out a review on energy conservation of construction machinery for pumping concrete. The research methodology comprises a quantitative analysis method and literature investigation method. First, the structure and working principle of construction machinery for pumping concrete are expounded, and energy consumption ways of construction machinery for pumping concrete are analyzed. Then, research developments in the energy conservation of construction machinery for pumping concrete are summarized. Finally, challenges with the energy conservation of construction machinery for pumping concrete are presented.
01 Jan 2017
TL;DR: In this article, a variable displacement control model was established under the physical constraint condition of non-collision between piston and cylinder, and the simulation and test results show that piston of concrete pumping system don't strike cylinder and reduce the hydraulic shock of the main pump outlet, meanwhile improve the response speed of the cylinder and achieve energy saving purposes under varying loads.
Abstract: To solve the problems of cylinder piston striking cylinder and the hydraulic shocking of the main pump, and causing energy waste problem, the method of variable displacement control of piston stroke was proposed. In order to achieve effective control of the piston stroke, variable displacement control model was established under the physical constraint condition of non-collision between piston and cylinder. And the control process was realized by Dynamic Programming(DP), the simulation and test results show that piston of concrete pumping system don’t strike cylinder and reduce the hydraulic shock of the main pump outlet, meanwhile improve the response speed of the cylinder and achieve energy-saving purposes under varying loads. This control model built in the integration design space of structure variable and control variable is of guiding significance for solving open-loop system’s engineering problems.
References
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TL;DR: In this paper, a hydraulic cylinder driven scheme combining a pressure compensator and an energy recovery device together has been proposed to achieve good control operation and energy saving capability simultaneously, and its efficiency characteristics are further investigated in order to provide analytical and experimental references to practical applications.
47 citations
TL;DR: In this paper, four main energy management strategies (EMSs) have been applied to hybrid electric wheel loaders (HEWLs) in order to evaluate and compare the energy saving effects of these strategies.
41 citations
TL;DR: It is shown that, for a common steering maneuver, a maximum of 20% of the energy required to complete the steering maneuver can be recovered and that the new EPAS function can be embedded in existing systems without changes to the hardware or the motor configuration.
Abstract: This paper describes a new function for electrical-power-assisted steering (EPAS) systems applied for hybrid electric trucks (HETs). EPAS systems consume power to provide torque to steer the wheels. The required power must be equal to the power caused by the self-alignment torque that forces the wheels back into the aligned position. This paper describes, for the first time, how self-alignment torque is used to recover energy that is required to turn the wheels. This paper shows that, for a common steering maneuver, a maximum of 20% of the energy required to complete the steering maneuver can be recovered. This energy saving relates to a fuel gain of 2094.5 gal over the lifetime of a truck of 500 000 mi. This paper also shows that the new EPAS function can be embedded in existing systems without changes to the hardware or the motor configuration. An EPAS model is developed in Dymola to show how steering at various vehicle speeds and various steering wheel angles contribute to the energy savings. An EPAS drive has been designed, constructed, and tested for an HET to validate the simulation results.
12 citations