Fuel Efficiency Optimization of a Baseline Wheel Loader and its Hydraulic Hybrid Variants Using Dynamic Programming

Heikkilä, Mikko; Huova, Mikko; Tammisto, Jyrki; Linjama, Matti; Tervonen, Jussi

doi:10.1115/fpmc2018-8853

Cited by 8 publications

(6 citation statements)

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“…In addition, researchers at Tampere University have worked on Digital Displacement ® . They have, amongst others, worked on Digital Displacement ® transformers [36,37,48].…”

Section: Individual Element Controlmentioning

confidence: 99%

Classification and Review of Variable Displacement Fluid Power Pumps and Motors

Kärnell

Ericson

2023

TJFP

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Displacement control of positive displacement machines has been a part of fluid power since the early days. Some of the early hydraulic presses already used two different displacement settings, though this was realised by using two different pumps rather than changing the displacement. Later, radial motors with variable stroke length appeared, followed by other designs of variable machines, such as swashplate machines, bent-axis machines, and variable vane machines. All these solutions control the displacement by varying the volume difference of the displacement element – but there are other ways of achieving this. Most have not passed the research state, but some are commercially available. In this paper, different ways of varying the displacement are presented and classified. The classification divides concepts into either control of displaced fluid or control of usage of displaced fluid. In turn, these concepts can be either on system level or displacement element level. This results in four main classes, which to some extent can describe the characteristics of the control.

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“…In addition, researchers at Tampere University have worked on Digital Displacement ® . They have, amongst others, worked on Digital Displacement ® transformers [36,37,48].…”

Section: Individual Element Controlmentioning

confidence: 99%

Classification and Review of Variable Displacement Fluid Power Pumps and Motors

Kärnell

Ericson

2023

TJFP

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“…Hydraulic transformers to recover the energy from loads and deliver it back to the same subsystems are also a possibility for energy efficiency improvement [23][24][25][26][27]. They can be seen as 'add-on' systems where a hydraulic machine is coupled at the meter-out port of the actuator.…”

Section: Examples Of Machine Architecturesmentioning

confidence: 99%

On Machine Learning-Based Control for Energy Management in Construction Machines

Raduenz

2022

Linköping Studies in Science and Technology. Dissertations

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High energy efficiency is a key requirement for modern construction machinery. This is because of stricter environmental targets, electrification, and reduction of operation costs. To meet this requirement, the powertrain architectures of the machines are becoming increasingly complex, for example through hybridisation of drivetrain and work functions, or with improved hydraulic systems. However, the more complex the architecture is, the harder the management of splitting power between different sources and consumers. The number of work functions, operating environments, and tasks these machines engage in, along with the added degrees of freedom with respect to how energy can be recovered, exchanged, and reused, makes them unique. Therefore, the development of control strategies for energy management in such machines requires specific research and development with their architecture and application in focus. This doctoral thesis presents an analysis of two methods for the development of machine learning-based energy management strategies for construction machines. One is based on supervised learning and the other on reinforcement learning. The methods use optimisation to find optimised solutions for the control problem of the systems and machine learning for learning and implementing the control decisions. In both methods, models of the physical systems are used for the learning and training. The thesis highlights and confirms, with experimental results, the potential of such methods to derive control strategies for these machines. The studied methods can learn and implement improved control decisions in the real systems that result in the potential for increased efficiency. At the same time, their robustness is shown in the application to unseen scenarios during training, although that does not eliminate the need for further training in the real systems after deployment. The thesis also increases the comprehensiveness on energy management for construction machines. The thesis was completed in a double-degree format between the

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“…His result shows great reduction in fuel consumption: 28% on the highway and 13% in city driving. Heikkilä et al used dynamic programming to optimize fuel efficiency on a wheel loader, also showing great energy savings [21]. Sprengel and Ivantysynova used neural network-based power management on a hydraulic hybrid transmission.…”

Section: Design Of Reference Ht Systemmentioning

confidence: 99%

Advanced Design and Optimal Sizing of Hydrostatic Transmission Systems

Guo

Vacca

2021

Actuators

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This paper presents a novel method for designing and sizing high-efficient hydrostatic transmissions (HTs) for heavy duty propulsion applications such as agricultural and construction machinery. The proposed method consists in providing cost effective HT architectures that maximizes efficiency at the most frequent operating conditions of the transmission, as opposed to the traditional HT design methods based on the most demanding requirements of the system. The sizing method is based on a genetic optimization algorithm for calculating the optimal displacement of the main units of the HT to maximizes the efficiency in the most frequent operating conditions of the vehicle. A simulation model for HTs is built in MATLAB/Simulink® environment to test three different circuit alternatives for basic HTs. Considering a particular 250 kW heavy-duty application for which drive cycle data were available, this study shows great improvement in energy efficiency (14%) and power saving (20.1%) at frequent operating conditions while still achieving the corner power condition.

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Fuel Efficiency Optimization of a Baseline Wheel Loader and its Hydraulic Hybrid Variants Using Dynamic Programming

Cited by 8 publications

References 0 publications

Classification and Review of Variable Displacement Fluid Power Pumps and Motors

Classification and Review of Variable Displacement Fluid Power Pumps and Motors

On Machine Learning-Based Control for Energy Management in Construction Machines

Advanced Design and Optimal Sizing of Hydrostatic Transmission Systems

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