scholarly journals Adaptive Smoothing Power Following Control Strategy Based on an Optimal Efficiency Map for a Hybrid Electric Tracked Vehicle

Energies ◽  
2020 ◽  
Vol 13 (8) ◽  
pp. 1893 ◽  
Author(s):  
Baodi Zhang ◽  
Sheng Guo ◽  
Xin Zhang ◽  
Qicheng Xue ◽  
Lan Teng
Keyword(s):  
Fuel Consumption ◽  
Control Strategy ◽  
Hydraulic Pump ◽  
Tracked Vehicle ◽  
Adaptive Smoothing ◽  
Equivalent Fuel ◽  
Insufficient Response ◽  
Hybrid Electric ◽  
Optimal Efficiency ◽  
Efficiency Map

The series hybrid electric powertrain is the main architecture of the hybrid electric tracked vehicle. For a series tracked hybrid electric bulldozer (HEB), frequent fluctuations of the engine working points, deviation of the genset working points from the pre-set target trajectory due to an insufficient response, or interference of the hydraulic pump consumed torque, will all result in increased fuel consumption. To solve the three problems of fuel economy, an adaptive smooth power following (ASPF) control strategy based on an optimal efficiency map is proposed. The strategy combines a fuzzy adaptive filter algorithm with a genset’s optimal efficiency, which can adaptively smooth the working points of the genset and search the trajectory for the genset’s best efficiency when the hydraulic pump torque is involved. In this study, the proposed strategy was compared on the established HEB hardware in loop (HIL) platform with two other strategies: a power following strategy in a preliminarily practical application (PF1) and a typical power following strategy based on the engine minimum fuel consumption curve (PF2). The results of the comparison show that (1) the proposed approach can significantly reduce the fluctuation and pre-set trajectory deviation of the engine and generator working points; (2) the ASPF strategy achieves a 7.8% improvement in the equivalent fuel saving ratio (EFSR) over the PF1 strategy, and a 3.4% better ratio than the PF2 strategy; and (3) the ASPF strategy can be implemented online with a practical controller.

Equivalent fuel consumption optimal control of a series hybrid electric vehicle

2009 ◽  
Vol 223 (8) ◽  
pp. 1003-1018 ◽  
Author(s):  
J-P Gao ◽  
G-M G Zhu ◽  
E G Strangas ◽  
F-C Sun
Keyword(s):  
Optimal Control ◽  
Fuel Consumption ◽  
Control Strategy ◽  
Supervisory Control ◽  
Hybrid Electric Vehicle ◽  
Combustion Engine ◽  
Optimal Control Strategy ◽  
Equivalent Fuel ◽  
Hybrid Electric ◽  
Equivalent Fuel Consumption

Improvements in hybrid electric vehicle fuel economy with reduced emissions strongly depend on their supervisory control strategy. In order to develop an efficient real-time supervisory control strategy for a series hybrid electric bus, the proposed equivalent fuel consumption optimal control strategy is compared with two popular strategies, thermostat and power follower, using backward simulations in ADVISOR. For given driving cycles, global optimal solutions were also obtained using dynamic programming to provide an optimization target for comparison purposes. Comparison simulations showed that the thermostat control strategy optimizes the operation of the internal combustion engine and the power follower control strategy minimizes the battery charging and discharging operations which, hence, reduces battery power loss and extends the battery life. The equivalent fuel consumption optimal control strategy proposed in this paper provides an overall system optimization between the internal combustion engine and battery efficiencies, leading to the best fuel economy.

scholarly journals Energy Control Strategy for Parallel Hybrid Electric Vehicle Based on Terminal Neural Network

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Haitao Yan ◽  
Yongzhi Xu
Keyword(s):  
Neural Network ◽  
Fuel Consumption ◽  
Electric Vehicle ◽  
Control Strategy ◽  
Hybrid Electric Vehicle ◽  
Energy Control ◽  
Time Performance ◽  
Equivalent Fuel ◽  
Hybrid Electric ◽  
Equivalent Fuel Consumption

Energy control strategy is a key technology of hybrid electric vehicle, and its control effect directly affects the overall performance of the vehicle. The current control strategy has some shortcomings such as poor adaptability and poor real-time performance. Therefore, a transient energy control strategy based on terminal neural network is proposed. Firstly, based on the definition of instantaneous control strategy, the equivalent fuel consumption of power battery was calculated, and the objective function of the minimum instantaneous equivalent fuel consumption control strategy was established. Then, for solving the time-varying nonlinear equations used to control the torque output, a terminal recursive neural network calculation method using BARRIER functions is designed. The convergence characteristic is analyzed according to the activation function graph, and then the stability of the model is analyzed and the time efficiency of the error converging to zero is deduced. Using ADVISOR software, the hybrid power system model is simulated under two typical operating conditions. Simulation results show that the hybrid electric vehicle using the proposed instantaneous energy control strategy can not only ensure fuel economy but also shorten the control reaction time and effectively improve the real-time performance.

Hierarchical energy management strategy considering switching schedule for a dual-mode hybrid electric vehicle

2021 ◽  
pp. 095440702110297
Author(s):  
Hui Liu ◽  
Rui Liu ◽  
Riming Xu ◽  
Lijin Han ◽  
Shumin Ruan
Keyword(s):  
Fuel Consumption ◽  
Energy Management ◽  
Control Strategy ◽  
Power Distribution ◽  
Hybrid Electric Vehicle ◽  
Hierarchical Control ◽  
Management Problem ◽  
Energy Management Strategy ◽  
Dual Mode ◽  
Hybrid Electric

Energy management strategies are critical for hybrid electric vehicles (HEVs) to improve fuel economy. To solve the dual-mode HEV energy management problem combined with switching schedule and power distribution, a hierarchical control strategy is proposed in this paper. The mode planning controller is twofold. First, the mode schedule is obtained according to the mode switch map and driving condition, then a switch hunting suppression algorithm is proposed to flatten the mode schedule through eliminating unnecessary switch. The proposed algorithm can reduce switch frequency while fuel consumption remains nearly unchanged. The power distribution controller receives the mode schedule and optimizes power distribution between the engine and battery based on the Radau pseudospectral knotting method (RPKM). Simulations are implemented to verify the effectiveness of the proposed hierarchical control strategy. For the mode planning controller, as the flattening threshold value increases, the fuel consumption remains nearly unchanged, however, the switch frequency decreases significantly. For the power distribution controller, the fuel consumption obtained by RPKM is 4.29% higher than that of DP, while the elapsed time is reduced by 92.53%.

Research on Modeling and Control Strategy of Parallel Hybrid Electric Back-Loading Compression Sanitation Vehicle

2013 ◽  
Vol 420 ◽  
pp. 355-362
Author(s):  
Rong Yang ◽  
Di Ming Lou ◽  
Pi Qiang Tan ◽  
Zhi Yuan Hu
Keyword(s):  
Fuel Consumption ◽  
Electric Vehicle ◽  
Control Strategy ◽  
Hybrid Electric Vehicle ◽  
Stable Operation ◽  
Parallel Hybrid Electric Vehicle ◽  
Fuel Consumption Reduction ◽  
Consumption Reduction ◽  
Parallel Hybrid ◽  
Hybrid Electric

Establish simulation models of the conventional and parallel hybrid electric back-loading compression sanitation vehicle by AVL CRUISE and MATLAB/Simulink software. Study on control strategy of parallel hybrid electric vehicle based on the work characteristics of back-loading compression sanitation. Results show that: about 24.5% fuel consumption reduction in hybrid modeling compared to the conventional sanitation vehicle under heavy commercial vehicle standard test cycle (C-WTVC, Adapted World Transient Vehicle Cycle), and battery SOC was little changed at 50%. About 32% fuel consumption reduction in hybrid compared to the conventional vehicle under the actual road testing spectrum, and SOC increased about 21.6% relative to the initial state. It controls the engine to work in more stable operation region and reduces engine idle time, but increases engine start-stop times. It also could provide some references for specific engine development of parallel hybrid electric vehicle

Research on Energy Saving Scheme of CVT in Automobile

2010 ◽  
Vol 37-38 ◽  
pp. 1017-1021
Author(s):  
Ping Yuan Xi ◽  
Limin Chen
Keyword(s):  
Energy Saving ◽  
Fuel Consumption ◽  
Fuel Economy ◽  
Control Strategy ◽  
Automatic Transmission ◽  
Mechanical Efficiency ◽  
Efficiency Curve ◽  
Variable Transmission ◽  
Optimal Efficiency ◽  
Continuous Range

The continuously variable transmission (CVT) offers the potential of allowing the engine operate near the optimal efficiency curve throughout a continuous range of velocity ratios. So the fuel economy of the automobile will be improved distinctly with the CVT having high mechanical efficiency. The double parameter shifting rule is used more frequently in the automatic transmission. The accurate model of CVT was developed and integrated with the control strategy in this paper. The CVT enables the engine to operate under the most economical conditions, which makes the fuel consumption be reduced and the efficiency be improved.

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