Optimization Tools Applied in the Design of a Hydraulic Hybrid Powertrain for Minimal Fuel Consumption

2021 ◽  
pp. 122-130
Author(s):  
Társis Prado Barbosa ◽  
Aline de Faria Lemos ◽  
Luiz Otávio Ferreira Gonçalves ◽  
Ricardo Poley Martins Ferreira ◽  
Leonardo Adolpho Rodrigues da Silva ◽  
...  
Keyword(s):  
Fuel Consumption ◽  
Hybrid Powertrain ◽  
Hydraulic Hybrid

Optimized Control Strategy Based on the Driving Cycle Type for a Hydraulic Hybrid Bus

2012 ◽  
Author(s):  
Ali Safaei ◽  
Vahid Esfahanian ◽  
Mohammad Reza Ha’iri-Yazdi ◽  
Mohsen Esfahanian ◽  
Masood Masih Tehrani ◽  
...  
Keyword(s):  
Fuel Consumption ◽  
Intelligent Control ◽  
Control Strategy ◽  
Dynamic Programming Algorithm ◽  
Driving Cycle ◽  
Programming Algorithm ◽  
Hybrid Powertrain ◽  
Hydraulic Hybrid ◽  
Hybrid Bus ◽  
Degree Of Similarity

Using hybrid powertrains is an attractive idea to reduce the fuel consumption in vehicles. Control strategy is the most challenging subject in designing of a hybrid powertrain. In this paper, an optimized control strategy based on the driving cycle type designed for a hydraulic hybrid bus has been presented. Because of considering the type of the driving cycle, the proposed control strategy can be named as an intelligent one. In this controller, at first, four standard driving cycles have been defined as the reference clusters. Then the optimized control strategy for each cluster has been derived using a dynamic programming algorithm. In addition, several multi-layered perceptron networks are modeled in order to use the output of each optimized control strategy. After that a clustering method with a feature selection algorithm has been implemented to assign degree of similarity to each cluster for the unknown driving cycle. Finally, a linear combination of four optimized control strategy outputs has been used for generating final output of the intelligent control strategy. In this combination, each output is weighted by the corresponding degree of similarity. Here, the hydraulic hybrid bus model is a feed forward one and has been simulated using a compound driving cycle. The compound driving cycle consists of six distinct 100s long portions of the Nuremburg driving cycle. The simulation results show that by using the intelligent control strategy, the fuel consumption of the hybrid bus has been reduced by almost 12% in comparison with the results of a rule-based control strategy.

Online optimization of Pontryagin’s minimum principle for a series hydraulic hybrid wheel loader

2021 ◽  
pp. 095440702110398
Author(s):  
Qi Zhang ◽  
Feng Wang ◽  
Bing Xu ◽  
Zongxuan Sun
Keyword(s):  
Dynamic Programming ◽  
Fuel Consumption ◽  
Minimum Principle ◽  
Pontryagin’S Minimum Principle ◽  
Energy Management Strategy ◽  
Hybrid Powertrain ◽  
Rule Based ◽  
Wheel Loader ◽  
Hydraulic Hybrid ◽  
Pontryagin's Minimum Principle

The hydraulic hybrid powertrain has great potential for reducing fuel consumption and emission of off-road vehicles. The energy management strategy is the key to hybrid powertrain and currently there are many well-developed strategies. Of which the Pontryagin’s minimum principle is of research interest since it is a global optimization method while less computational burden than dynamic programming. However, it requires full cycle information to calculate co-state value in the principle, making it not implementable. Therefore in this study an implementable Pontryagin’s minimum principle is proposed for a series hybrid wheel loader, where the optimal co-state value in the principle is trained through repetitive wheel loader duty cycle. The Pontryagin’s minimum principle formulations of hybrid wheel loader are developed. The online co-state training algorithm is presented. A dynamic simulation model of hybrid wheel loader is developed. The fuel consumption of hybrid wheel loader with proposed strategy is compared with dynamic programming strategy and rule-based strategy in wheel loader long and short loading cycles. Results show the fuel consumption with proposed strategy is close to dynamic programming result and is lower than rule-based strategy. Finally, the influence of pressure level of hybrid powertrain on vehicle fuel consumption is studied.

Predictive Energy Management for Parallel Hydraulic Hybrid Passenger Vehicle

2010 ◽  
Author(s):  
Timothy O. Deppen ◽  
Andrew G. Alleyne ◽  
Kim A. Stelson ◽  
Jonathan J. Meyer
Keyword(s):  
Energy Management ◽  
Hybrid Vehicle ◽  
Management Problem ◽  
Transfer Energy ◽  
Hybrid Powertrain ◽  
Engine Torque ◽  
Engine Simulation ◽  
Hydraulic Hybrid ◽  
Displacement Pump ◽  
Hydraulic Hybrid Vehicle

In this paper, a model predictive control (MPC) approach is presented for solving the energy management problem in a parallel hydraulic hybrid vehicle. The hydraulic hybrid vehicle uses variable displacement pump/motors to transfer energy between the mechanical and hydraulic domains and a high pressure accumulator for energy storage. A model of the parallel hydraulic hybrid powertrain is presented which utilizes the Simscape/Simhydraulics toolboxes of Matlab. These toolboxes allow for a concise description of the relevant powertrain dynamics. The proposed MPC regulates the engine torque and pump/motor displacement in order to track a desired velocity profile while maintaining desired engine conditions. In addition, logic is applied to the MPC to prevent high frequency cycling of the engine. Simulation results demonstrate the capability of the proposed control strategy to track both a desired engine torque and vehicle velocity.

scholarly journals Development of Hybrid Vehicle Energy Consumption Model for Transportation Applications—Part II: Traction Force-Speed Based Energy Consumption Modeling

2019 ◽  
Vol 10 (2) ◽  
pp. 22 ◽  
Author(s):  
Siriorn Pitanuwat ◽  
Hirofumi Aoki ◽  
Satoru IIzuka ◽  
Takayuki Morikawa
Keyword(s):  
Energy Consumption ◽  
Fuel Consumption ◽  
Traction Force ◽  
Hybrid Vehicles ◽  
Specific Power ◽  
Mode Transition ◽  
Hybrid Powertrain ◽  
Modeling Methods ◽  
Consumption Model ◽  
Energy Consumption Modeling

In the transportation sector, the fuel consumption model is a fundamental tool for vehicles’ energy consumption and emission analysis. Over the past decades, vehicle-specific power (VSP) has been enormously adopted in a number of studies to estimate vehicles’ instantaneous driving power. Then, the relationship between the driving power and fuel consumption is established as a fuel consumption model based on statistical approaches. This study proposes a new methodology to improve the conventional energy consumption modeling methods for hybrid vehicles. The content is organized into a two-paper series. Part I captures the driving power equation development and the coefficient calibration for a specific vehicle model or fleet. Part II focuses on hybrid vehicles’ energy consumption modeling, and utilizes the equation obtained in Part I to estimate the driving power. Also, this paper has discovered that driving power is not the only primary factor that influences hybrid vehicles’ energy consumption. This study introduces a new approach by applying the fundamental of hybrid powertrain operation to reduce the errors and drawbacks of the conventional modeling methods. This study employs a new driving power estimation equation calibrated for the third generation Toyota Prius from Part I. Then, the Traction Force-Speed Based Fuel Consumption Model (TFS model) is proposed. The combination of these two processes provides a significant improvement in fuel consumption prediction error compared to the conventional VSP prediction method. The absolute maximum error was reduced from 57% to 23%, and more than 90% of the predictions fell inside the 95% confidential interval. These validation results were conducted based on real-world driving data. Furthermore, the results show that the proposed model captures the efficiency variation of the hybrid powertrain well due to the multi-operation mode transition throughout the variation of the driving conditions. This study also provides a supporting analysis indicating that the driving mode transition in hybrid vehicles significantly affects the energy consumption. Thus, it is necessary to consider these unique characteristics to the modeling process.

scholarly journals Simulation Study of Advanced Variable Displacement Engine Coupled to Power-Split Hydraulic Hybrid Powertrain

2009 ◽  
Author(s):  
Fernando Tavares ◽  
Rajit Johri ◽  
Zoran Filipi
Keyword(s):  
Hybrid Powertrain ◽  
Cylinder Deactivation ◽  
Integrated Simulation ◽  
Engine Model ◽  
Hydraulic Hybrid ◽  
Wide Range ◽  
Power Split ◽  
Variable Displacement ◽  
Mode Transitions ◽  
And Control

The simulation-based investigation of the variable displacement engine is motivated by a desire to enable unthrottled operation at part load, and hence eliminate pumping losses. The mechanism modeled in this work is derived from a Hefley engine concept. Other salient features of the proposed engine are turbocharging and cylinder deactivation. The cylinder deactivation combined with variable displacement further expands the range of unthrottled operation, while turbocharging increases the power density of the engine and allows downsizing without the loss of performance. While the proposed variable displacement turbocharged engine (VDTCE) concept enables operations in a very wide range, running near idle is impractical. Therefore, the VDTCE is integrated with a hybrid powertrain allowing flexibility in operating the engine, elimination of idling and mitigation of possible issues with engine transients and mode transitions. The engine model is developed in AMESim using physical principles and 1-D gas dynamics. A predictive model of the power-split hydraulic hybrid driveline is created in SIMULINK, thus facilitating integration with the engine. The integrated simulation tool is utilized to address design and control issues, before determining the fuel economy potential of the powertrain comprising a VDTCE engine and a hydraulic hybrid driveline.

scholarly journals Study and Simulation of a Hydraulic Hybrid Powertrain

2017 ◽  
Vol 126 ◽  
pp. 1131-1138 ◽  
Author(s):  
Alarico Macor ◽  
Alberto Benato ◽  
Antonio Rossetti ◽  
Zeno Bettio
Keyword(s):  
Hybrid Powertrain ◽  
Hydraulic Hybrid

Optimal Energy Use in a Light Weight Hydraulic Hybrid Passenger Vehicle

2012 ◽  
Vol 134 (4) ◽  
Author(s):  
Timothy O. Deppen ◽  
Andrew G. Alleyne ◽  
Kim A. Stelson ◽  
Jonathan J. Meyer
Keyword(s):  
Predictive Control ◽  
Control Strategy ◽  
Management Strategy ◽  
Energy Use ◽  
Individual Component ◽  
Light Weight ◽  
Passenger Vehicle ◽  
Energy Management Strategy ◽  
Hybrid Powertrain ◽  
Hydraulic Hybrid

In this study we present a procedure for the design and implementation of a control strategy to optimize energy use within a light weight hydraulic hybrid passenger vehicle. The hydraulic hybrid utilizes a high pressure accumulator for energy storage which has superior power density than conventional battery technology. This makes fluid power attractive for urban driving applications in which there are frequent starts and stops and large startup power demands. A dynamic model of a series hydraulic hybrid powertrain is presented along with the design of a model predictive control based energy management strategy. Model predictive control was chosen for this study because it uses no future information about the drive cycle in its design. This increases the flexibility of the controller allowing it to be directly applied to a variety of drive cycles. Using the model predictive framework, a holistic view of the powertrain was taken in the design of the control strategy, and the impact of each actuator’s efficiency on overall efficiency was evaluated. A hardware-in-the-loop experiment using an electro-hydraulic powertrain testbed was then used to validate the dynamic model and control performance. Through a simulation study in which each actuator’s efficiency was given varying levels of priority in the objective function, it was found that overall system efficiency could be improved by allowing for small sacrifices in individual component performance. In fact, the conventional wisdom of using the additional degrees of freedom within a hybrid powertrain to optimize engine efficiency was found to yield the lowest overall powertrain efficiency. In this work we present a rigorous framework for the design of an energy management strategy. The design method improves the powertrain’s operational efficiency by finding the best balance between optimizing individual component efficiencies. Furthermore, since the design of the control strategy is built upon an analysis of individual components, it can be readily extended to other architectures employing different actuators.

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