Predictive power-split system of hybrid ship propulsion for energy management and emissions reduction

2021 ◽  
Vol 111 ◽  
pp. 104795
Author(s):  
Nikolaos Planakis ◽  
George Papalambrou ◽  
Nikolaos Kyrtatos
Keyword(s):  
Energy Management ◽  
Predictive Power ◽  
Emissions Reduction ◽  
Ship Propulsion ◽  
Power Split ◽  
Split System

Robust augmented H∞ shift control strategy for power-split system with a two-speed AMT gearbox of a heavy commercial vehicle

2020 ◽  
pp. 095440702097709
Author(s):  
Xiaohua Zeng ◽  
Zhenwei Wang ◽  
Dafeng Song ◽  
Dongpo Yang
Keyword(s):  
Control Strategy ◽  
Commercial Vehicle ◽  
Kinetic Equations ◽  
Substantial Improvement ◽  
Transmission System ◽  
Power Sources ◽  
Shift Control ◽  
Power Split ◽  
Heavy Commercial Vehicle ◽  
Split System

The coordination control of a transmission system has gradually attracted more attention with the development of hybrid electric vehicles. However, nonlinear coupling of multiple power sources, superposition of different dynamic characteristics in multiple components, and withdrawal and intervention for a power-split powertrain with a two-speed automated manual transmission (AMT) gearbox can cause jerk and vibration of the transmission system during the shift, which has higher requirements and challenges for the overall performance improvement of the system. This paper designs a novel, robust, augmented H∞ shift control strategy for a power-split system with a two-speed AMT gearbox of a heavy commercial vehicle and verifies the strategy’s effectiveness with simulations and experiments. First, the dynamic plant model and kinetic equations are established, and the shift is divided into five stages to clearly reveal the jerk and vibration problem. Based on augmented theory, a robust H∞ shift control strategy is proposed. Shift coordination is transformed into a speed tracking problem, and state variable and disturbance are reconstructed to obtain a new augmented system. Simulation and hardware-in-the-loop test are carried out to verify the effectiveness of the strategy, which mainly includes simulation of pneumatic actuator and H∞ control strategy. Results show that the proposed H∞ control strategy can greatly reduce the jerk of the transmission system. The jerk produced by the proposed strategy is decreased from 20.4 to 4.07 m/s3, leading to a substantial improvement of 80%. Therefore, the proposed strategy may offer a theoretical reference for the actual vehicle controller during the shift.

Development of Energy Management Strategies for Heavy Mobile Machinery

2013 ◽  
Author(s):  
Antti Lajunen
Keyword(s):  
Energy Consumption ◽  
Energy Management ◽  
Underground Mining ◽  
Management Strategies ◽  
Operating Efficiency ◽  
Optimal Power ◽  
Power Split ◽  
Electric Loader ◽  
Mobile Machinery ◽  
Task Oriented

This paper introduces a method for developing energy management strategies (EMS) for task-oriented heavy mobile machinery. The case application is a hybrid underground mining loader but the method is also used for a diesel-electric and electric loader. Depending on the optimization target, the sequence for optimal power-split between the engine-generator (gen-set) and battery is defined. The minimization of the energy consumption and maximization of the operating efficiency are used as the optimization targets. The developed method is based on dynamic programming simulations which generate the optimal power-split for the evaluation of the control parameters. The simulation results showed that there are no significant differences between the two optimization targets in terms of the control sequence of the hybrid loader. The major difference was observed in the battery charging power which was much lower in the case of the minimization of the energy consumption.

Velocity Optimization and Robust Energy Management of Connected Power-Split Hybrid Electric Vehicles

2021 ◽  
Author(s):  
Seyedeh Mahsa Sotoudeh ◽  
Baisravan HomChaudhuri
Keyword(s):  
Energy Management ◽  
Time Horizon ◽  
Control Method ◽  
Optimization Approach ◽  
Management Problem ◽  
Energy Management Strategy ◽  
Short Term ◽  
Power Split ◽  
Energy Manager

Abstract This paper focuses on an eco-driving based hierarchical robust energy management strategy for connected automated HEVs in the presence of uncertainty. The proposed control strategy includes a velocity optimizer, which evaluates the optimal vehicle velocity, and a powertrain energy manager, which evaluates the optimal power split between the engine and the battery in a hierarchical framework. The velocity optimizer accounts for regenerative braking and minimizes the total driving power and friction braking over a short control horizon. The hierarchical powertrain energy manager employs a long- and short-term strategy where it first approximately solves its problem over a long time horizon (the whole trip time in this paper) using the traffic data obtained from vehicle-to-infrastructure (V2I) connectivity. This is followed by a short-term decision maker that utilizes the velocity optimizer and long-term solution, and solves the energy management problem over a relatively short time horizon using robust prediction control methods to factor in any uncertainty in the velocity profile due to uncertain traffic. We solve the long-term energy management problem using pseudospectral optimal control method, and the short-term problem using robust tube-based model predictive control(MPC) method. Simulation results show the competence of our proposed approach, where our proposed co-optimization approach with long- and short-term solution results in ≈ 12% more energy efficiency than a baseline co-optimization approach.

Optimal integrated energy management and shift control in parallel hybrid electric vehicles with dual-clutch transmission

2019 ◽  
Vol 234 (2-3) ◽  
pp. 599-609
Author(s):  
Guoqiang Li ◽  
Daniel Görges
Keyword(s):  
Fuel Consumption ◽  
Energy Management ◽  
Electric Vehicles ◽  
Hybrid Electric Vehicles ◽  
Weighting Factor ◽  
Engine Torque ◽  
Shift Control ◽  
Parallel Hybrid ◽  
Power Split ◽  
Hc Emissions

This paper addresses the integration of the energy management and the shift control in parallel hybrid electric vehicles with dual-clutch transmission to reduce the fuel consumption, decrease the pollutant emissions, and improve the driving comfort simultaneously. Dynamic programming with a varying weighting factor in the cost function is proposed to balance the shift frequency and the fuel consumption for the power-split control and gear schedule design. Simulation results present that the drivability can be improved with a varying weighting factor due to fewer shift events while the fuel consumption is only slightly increased compared to dynamic programming with a constant weighting factor. A shift-energy-management strategy integrating the upshift and power-split control based on a multi-objective optimization is presented where model predictive control is employed to ensure engine load rate constraints. The strategy can smoothen the engine torque through torque compensation from the electric motor to prevent engine transient emissions resulting from a sudden load change. In a simulation study, the NOx and HC emissions could be reduced by 1.4% and 2.6% with 2% increase of the overall fuel consumption for the Federal Test Procedure 75 by smoothening the engine torque. For the New European Driving Cycle, 0.9% and 1.1% reduction of NOx and HC emissions could be achieved with only 0.3% more fuel consumption.

Investigation on the Energy Management Strategy for Hydraulic Hybrid Wheel Loaders

2013 ◽  
Author(s):  
Feng Wang ◽  
Mohd Azrin Mohd Zulkefli ◽  
Zongxuan Sun ◽  
Kim A. Stelson
Keyword(s):  
Energy Management ◽  
Hydraulic System ◽  
Management Strategy ◽  
Energy Management Strategy ◽  
Road Vehicles ◽  
Engine Operation ◽  
Wheel Loader ◽  
Hydraulic Hybrid ◽  
Power Split ◽  
Wheel Loaders

Energy management strategies for a hydraulic hybrid wheel loader are studied in this paper. The architecture of the hydraulic hybrid wheel loader is first presented and the differences of the powertrain and the energy management system between on-road vehicles and wheel loaders are identified. Unlike the on-road vehicles where the engine only powers the drivetrain, the engine in a wheel loader powers both the drivetrain and the working hydraulic system. In a non-hybrid wheel loader, the two sub-systems interfere with each other since they share the same engine shaft. By using a power split drivetrain, it not only allows for optimal engine operation and regenerative braking, but also eliminates interferences between driving and working functions, which improve the productivity, fuel efficiency and operability of the wheel loader. An energy management strategy (EMS) based on dynamic programming (DP) is designed to optimize the operation of both the power split drivetrain and the working hydraulic system. A short loading cycle is selected as the duty cycle. The EMS based on DP is compared with a rule-based strategy through simulation.

scholarly journals Modeling and energy management strategy research of a power-split hybrid electric vehicle

2020 ◽  
Vol 12 (10) ◽  
pp. 168781402096262
Author(s):  
Yupeng Zou ◽  
Ruchen Huang ◽  
Xiangshu Wu ◽  
Baolong Zhang ◽  
Qiang Zhang ◽  
...  
Keyword(s):  
Electric Vehicle ◽  
Energy Management ◽  
Fuel Economy ◽  
Hybrid Electric Vehicle ◽  
Research Work ◽  
Energy Management Strategy ◽  
Power Sources ◽  
Power Split ◽  
Hybrid Electric ◽  
The Impact

A power-split hybrid electric vehicle with a dual-planetary gearset is researched in this paper. Based on the lever analogy method of planetary gearsets, the power-split device is theoretically modeled, and the driveline simulation model is built by using vehicle modeling and simulation toolboxes in MATLAB. Six operation modes of the vehicle are discussed in detail, and the kinematic constraint behavior of power sources are analyzed. To verify the rationality of the modeling, a rule-based control strategy (RB) and an adaptive equivalent consumption minimization strategy (A-ECMS) are designed based on the finite state machine and MATLAB language respectively. In order to demonstrate the superiority of A-ECMS in fuel-saving and to explore the impact of different energy management strategies on emission, fuel economy and emission performance of the vehicle are simulated and analyzed under UDDS driving cycle. The simulation results of the two strategies are compared in the end, shows that the modeling is rational, and compared with RB strategy, A-ECMS ensures charge sustaining better, enables power sources to work in more efficient areas, and improves fuel economy by 8.65%, but significantly increases NOx emissions, which will be the focus of the next research work.

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