Jerk Analysis of a Power-Split Hybrid Electric Vehicle Based on a Data-Driven Vehicle Dynamics Model

Abstract

Given its highly coupled multi-power sources with diverse dynamic response characteristics, the mode transition process of a power-split Hybrid Electric Vehicle (HEV) can easily lead to unanticipated passenger-felt jerks. Moreover, difficulties in parameter estimation, especially power-source dynamic torque estimation, result in new challenges for jerk reduction. These two aspects entangle with each other and constitute a complicated coupling problem which obstructs the realization of a valid anti-jerk method. In this study, a vehicle dynamics model with reference to a data-driven modeling method is first established, integrating a full-time artificial neural network engine dynamic model that can accurately predict engine dynamic torque. Then the essential reason for the occurrence of vehicle jerks in real driving conditions is analyzed. Finally, to smooth the mode transition process, a more practical anti-jerk strategy based on power-source torque changing rate limitation (TCRL) is proposed. Verification studies indicate that the data-driven vehicle dynamics model has enough accuracy to reflect the vehicle dynamic characteristics, and the proposed TCRL strategy could reduce the vehicle jerk by up to 85.8%, without any sacrifice of vehicle performance. This research provides a feasible method for precise modeling of vehicle dynamics and a reference for improving the riding comfort of hybrid electric vehicles.

Jerk within the Context of Science and Engineering—A Systematic Review

“…Ride comfort is an important parameter in amusement rides [1,4,5], sea-keeping [9,10,122,126] and traditional land-based vehicles [12,25,45,95,[98][99][100][101][102][103][104][105][106]108,109,[111][112][113]115,[118][119][120][121][123][124][125][127][128][129][130][131]. There are still discussions ongoing regarding the significance of jerk regarding ride comfort for vehicles, and jerk is probably a better measure for driving comfort than acceleration, as pointed out by van Santen [128] and confirmed, e.g., in the study by Grant and Haycock [107].…”

Review on multi‐power sources dynamic coordinated control of hybrid electric vehicle during driving mode transition process

“…According to the result, DDPC exhibited superior mode switching quality compared with traditional model‐predictive control (MPC) based on mechanical models. Zeng et al built an integrated data‐driven vehicle dynamics model by training data collected from actual vehicle operation, such as engine speed, fuel rate, torque data, and motor speed, load signal, and so forth. Then, the anti‐jerk coordinated control strategy by limiting the torque change rate of the power source was raised.…”

Modeling and Dynamic Response Analysis of a Compound Power-Split Hybrid Electric Vehicle During the Engine Starting Process

“…Tang [26][27][28] established a vehicle dynamics model including the engine pulsating torque, engine mounting system, transmission system, suspension system, and vehicle body, and analyzed the resonance characteristics of a powersplit HEV in the processes of engine starting and stopping. Zeng [29][30] established a power-split HEV model including an engine model based on a BP neural network, and found that the torque change rate of the power source is the main reason for large vehicle jerk during the mode switching process. Using experimental data from a powersplit HEV, Liu [31][32] found that the longitudinal vibration of the seat track was most affected by the engine initial angle during the engine starting process.…”