Collaborative optimization and energy management of hydraulic hybrid mining trucks

2021 ◽  
pp. 095440702110585
Author(s):  
Hongliang Li ◽  
Denglin Zhu ◽  
Lihua Shang ◽  
Ping Fan
Keyword(s):  
Fuel Consumption ◽  
Energy Management ◽  
Extraction Method ◽  
Management Strategy ◽  
Transmission System ◽  
Collaborative Optimization ◽  
Energy Management Strategy ◽  
System Parameters ◽  
Hydraulic Hybrid ◽  
Driving Conditions

This article discusses the fuel economy optimization of a parallel hydraulic hybrid mining truck (HHMT). Considering the influences of various coupled factors, such as the transmission system, energy management strategy, and driving conditions, on the optimization goal, this article proposes the use of a double-layer optimization strategy with a collaborative optimization algorithm that combines particle swarm optimization (PSO) and a dynamic programming algorithm (DP) to eliminate the mutual effects of these coupled factors. A two-layer optimization model is developed, with powertrain parameters and energy management parameters as the optimization variables and the average fuel consumption under various driving conditions as the target. This model combines a variety of driving conditions to perform global optimization of the transmission system parameters while calculating the optimal energy distribution and analyzing the influences of various factors on the optimization goal. To achieve real-time and reliable control of energy management, the optimal energy management strategy rules obtained under various driving conditions are integrated and extracted, and an improved extraction method compared with the traditional extraction method is proposed. Finally, a rule-based energy management strategy is established. The strategy and optimized transmission system parameters are simulated and verified using a MATLAB and AMESIM joint simulation platform, and the effect of the rule strategy is evaluated. The obtained fuel consumption results are close to the results obtained by PSO-DP optimization, and the strategy is robust. The experiment verifies the effectiveness, feasibility and reliability of the optimization scheme, and extraction rule control strategy.

scholarly journals Power-Following Control Strategy of a Wheel-Drive Hydraulic Hybrid Vehicle

2020 ◽  
Vol 66 (3) ◽  
pp. 193-202
Author(s):  
Tao Zhang ◽  
Qiang Wang ◽  
Xiao-Hui He ◽  
Si-Sheng Li ◽  
Xin-Min Shen
Keyword(s):  
Fuel Consumption ◽  
Energy Management ◽  
Fuel Economy ◽  
Control Strategy ◽  
Management Strategy ◽  
Dynamic Performance ◽  
Energy Management Strategy ◽  
Hydraulic Hybrid ◽  
Wheel Drive ◽  
Critical Technology

Energy management strategy is a critical technology for improving the fuel economy of wheel-drive hydraulic hybrid vehicles. For driving, a power-following control strategy is proposed in this study by adding several working points of the engine in the optimal fuel economy power curve. For braking, the “I” curve distribution strategy based on critical braking strength zmin was adopted. A test bench was constructed according to the quarter of the prototype vehicle. Taking the typical working conditions of Federal Urban Driving Schedule (FUDS) and the selfset extra-urban driving schedule (EUDC-1) cycle condition into consideration, the energy management strategy was studied. The torque and speed of the simulated engine and pressure of the accumulator were obtained. The test fuel consumption in this research was compared with the original fuel consumption of the prototype vehicle. It was found that the proposed energy management strategy could effectively improve the fuel economy by more than 24 % under the requirement of satisfying the dynamic performance of the whole vehicle.

scholarly journals Adaptive Rule-Based Energy Management Strategy for a Parallel HEV

Energies ◽  
2019 ◽  
Vol 12 (23) ◽  
pp. 4472 ◽  
Author(s):  
Rishikesh Mahesh Bagwe ◽  
Andy Byerly ◽  
Euzeli Cipriano dos Santos ◽  
Ben-Miled
Keyword(s):  
Fuel Consumption ◽  
Energy Management ◽  
Duty Cycle ◽  
Management Strategy ◽  
Hybrid Electric Vehicle ◽  
Detailed Knowledge ◽  
Energy Management Strategy ◽  
Rule Based ◽  
Engine Efficiency ◽  
Efficiency Map

This paper proposes an Adaptive Rule-Based Energy Management Strategy (ARBS EMS) for a parallel hybrid electric vehicle (HEV). The aim of the strategy is to facilitate the aftermarket hybridization of medium- and heavy-duty vehicles. ARBS can be deployed online to optimize fuel consumption without any detailed knowledge of the engine efficiency map of the vehicle or the entire duty cycle. The proposed strategy improves upon the established Preliminary Rule-Based Strategy (PRBS), which has been adopted in commercial vehicles, by dynamically adjusting the regions of operations of the engine and the motor. It prevents the engine from operating in highly inefficient regions while reducing the total equivalent fuel consumption of the vehicle. Using an HEV model developed in Simulink®, both the proposed ARBS and the established PRBS strategies are compared over an extended duty cycle consisting of both urban and highway segments. The results show that ARBS can achieve high MPGe with different thresholds for the boundary between the motor region and the engine region. In contrast, PRBS can achieve high MPGe only if this boundary is carefully established from the engine efficiency map. This difference between the two strategies makes the ARBS particularly suitable for aftermarket hybridization where full knowledge of the engine efficiency map may not be available.

scholarly journals Research on energy management strategy considering battery life for plug-in hybrid electric vehicle

2018 ◽  
Vol 10 (9) ◽  
pp. 168781401879776 ◽  
Author(s):  
Jianjun Hu ◽  
Zhihua Hu ◽  
Xiyuan Niu ◽  
Qin Bai
Keyword(s):  
Fuel Consumption ◽  
Electric Vehicle ◽  
Energy Management ◽  
Management Strategy ◽  
Hybrid Electric Vehicle ◽  
Battery Life ◽  
Energy Management Strategy ◽  
Driving Cycles ◽  
Comprehensive Test ◽  
Hybrid Electric

To improve the fuel efficiency and battery life-span of plug-in hybrid electric vehicle, the energy management strategy considering battery life decay is proposed. This strategy is optimized by genetic algorithm, aiming to reduce the fuel consumption and battery life decay of plug-in hybrid electric vehicle. Besides, to acquire better drive-cycle adaptability, driving patterns are recognized with probabilistic neural network. The standard driving cycles are divided into urban congestion cycle, highway cycle, and urban suburban cycle; the optimized energy management strategies in three representative driving cycles are established; meanwhile, a comprehensive test driving cycle is constructed to verify the proposed strategies. The results show that adopting the optimized control strategies, fuel consumption, and battery’s life decay drop by 1.9% and 3.2%, respectively. While using the drive-cycle recognition, the features of different driving cycles can be identified, and based on it, the vehicle can choose appropriate control strategy in different driving conditions. In the comprehensive test driving cycle, after recognizing driving cycles, fuel consumption and battery’s life decay drop by 8.6% and 0.3%, respectively.

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 Real-time Energy Management Strategy for Oil-Electric-Liquid Hybrid System based on Lowest Instantaneous Energy Consumption Cost

Energies ◽  
2020 ◽  
Vol 13 (4) ◽  
pp. 784 ◽  
Author(s):  
Yang Yang ◽  
Zhen Zhong ◽  
Fei Wang ◽  
Chunyun Fu ◽  
Junzhang Liao
Keyword(s):  
Global Optimization ◽  
Real Time ◽  
Energy Management ◽  
Management Strategy ◽  
Threshold Energy ◽  
Energy Management Strategy ◽  
Hydraulic Hybrid ◽  
Consumption Cost ◽  
Saving Effect ◽  
Instantaneous Energy

For the oil–electric–hydraulic hybrid power system, a logic threshold energy management strategy based on the optimal working curve is proposed, and the optimal working curve in each mode is determined. A genetic algorithm is used to determine the optimal parameters. For driving conditions, a real-time energy management strategy based on the lowest instantaneous energy cost is proposed. For braking conditions and subject to the European Commission for Europe (ECE) regulations, a braking force distribution strategy based on hydraulic pumps/motors and supplemented by motors is proposed. A global optimization energy management strategy is used to evaluate the strategy. Simulation results show that the strategy can achieve the expected control target and save about 32.14% compared with the fuel consumption cost of the original model 100 km 8 L. Under the New European Driving Cycle (NEDC) working conditions, the energy-saving effect of this strategy is close to that of the global optimization energy management strategy and has obvious cost advantages. The system design and control strategy are validated.

Power Optimization of Series Hydraulic Hybrid Powertrain for Compact Wheel Loader

2019 ◽  
Author(s):  
Qunya Wen ◽  
Feng Wang ◽  
Bing Xu ◽  
Zongxuan Sun
Keyword(s):  
Energy Management ◽  
Fuel Economy ◽  
Management Strategy ◽  
Power Optimization ◽  
Parameter Study ◽  
Energy Management Strategy ◽  
Hybrid Powertrain ◽  
Wheel Loader ◽  
Hydraulic Hybrid ◽  
Equivalent Consumption Minimization Strategy

Abstract As an effective approach to improving the fuel economy of heavy duty vehicles, hydraulic hybrid has shown great potentials in off-road applications. Although the fuel economy improvement is achieved through different hybrid architectures (parallel, series and power split), the energy management strategy is still the key to hydraulic hybrid powertrain. Different optimization methods provide powerful tools for energy management strategy of hybrid powertrain. In this paper a power optimization method based on equivalent consumption minimization strategy has been proposed for a series hydraulic hybrid wheel loader. To show the fuel saving potential of the proposed strategy, the fuel consumption of the hydraulic hybrid wheel loader with equivalent consumption minimization strategy was investigated and compared with the system with a rule-based strategy. The parameter study of the equivalent consumption minimization strategy has also been conducted.

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