Journal of Jilin University(Engineering and Technology Edition) ›› 2022, Vol. 52 ›› Issue (7): 1679-1686.doi: 10.13229/j.cnki.jdxbgxb20210117

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Online optimization method of hybrid electric vehicle's engine optimal operating line

Yun-feng HU1,2(),Bao-lin MA2,Jia-mei LIN1,Xun GONG3,Xue-jun LI4   

  1. 1.State Key Laboratory of Automotive Simulation and Control，Jilin University，Changchun 130022，China
    2.College of Communication Engineering，Jilin University，Changchun 130022，China
    3.College of Artificial Intelligence，Jilin University，Changchun 130012，China
    4.School of Electronic Information Engineering，Changchun University，Changchun 130022，China
  • Received:2021-02-05 Online:2022-07-01 Published:2022-08-08

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Abstract:

In view of the large workload of off-line bench calibration of the optimal operating line （OOL） of hybrid electric vehicle engines， and the difficulty of obtaining the optimal speed under actual road conditions， an online optimization method for the optimal operating line of hybrid electric vehicle engines was proposed. First， a hybrid electric vehicle simulation model was established， and the accuracy of the model was verified through simulations under winter urban condition. Secondly， a target gradient estimation method based on recursive least squares （RLS） with forgetting factor was proposed，the accurate calculation of the specific fuel consumption target gradient in the process of optimizing the optimal operating line was realized using the real?time data. Then， an online optimization method for the optimal operating point of the engine based on gradient descent was proposed to realize the real-time calculation of the optimal engine speed. The comparative simulation of traditional calibration methods verifies the superiority of proposed method in real-time and control effect.

Key words: power split hybrid electrical vehicle, optimal operating line, online optimization, gradient descent, recursive least squares

CLC Number: 

  • TK401

Fig.1

Relation of engine instantaneous fuel consumption correction factor and coolant temperature"

Fig.2

Relationship between open circuit voltage， internal resistance and state of charge of battery"

Fig.3

Model verification results in real road condition"

Fig.4

Implementation diagram of online learning of optimal operating point under engine smooth power"

Fig.5

Optimization flow chart of engine's optimal operating point"

Fig.6

Simulink model diagram of power split hybrid electric vehicle"

Table 1

Hybrid electric vehicle parameter table"

参 数数 值参 数数 值
整车质量/kg1254空气比热容/［J·（kg·K）-1］1003
车轮半径/m0.287空气密度/（kg·m-3）1.2
迎风面积/m22.520滚动阻力系数0.015
空气阻力系数0.3电池容量/（A·h）6.5

Fig.7

Time history of engine speed with GD+RLS approach （engine output power 50 kW）"

Fig.8

Computation time of engine optimal operating point online optimization"

Fig.9

Comparison diagram of online optimization and calibration OOL under warm machine condition （simulation without aging）"

Fig.10

OOL obtained by online optimization in non-warm state （simulation without aging）"

Fig.11

OOL obtained by online optimization in warm state （simulation with aging）"

Fig.12

Fuel consumption comparison under UDDS condition， （simulation without aging）"

Fig.13

Fuel consumption comparison under UDDS condition （simulation with aging）"

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