The energy management strategy has a great influence on the fuel economy of hybrid electric vehicles, and the equivalent consumption minimization strategy (ECMS) has proved to be a useful tool for the real-time optimal control of Hybrid Electric Vehicles (HEVs). However, the adaptation of the equivalent factor poses a major challenge in order to obtain optimal fuel consumption as well as robustness to varying driving cycles. In this paper, an adaptive-ECMS based on driving pattern recognition (DPR) is established for hybrid electric vehicles with continuously variable transmission. The learning vector quantization (LVQ) neural network model was adopted for the on-line DPR algorithm. The influence of the battery state of charge (SOC) on the optimal equivalent factor was studied under different driving patterns. On this basis, a method of adaptation of the equivalent factor was proposed by considering the type of driving pattern and the battery SOC. Besides that, in order to enhance drivability, penalty terms were introduced to constrain frequent engine on/off events and large variations of the continuously variable transmission (CVT) speed ratio. Simulation results showed that the proposed method efficiently improved the equivalent fuel consumption with charge-sustaining operations and also took into account driving comfort.

Power-split hybrid electric vehicles (power-split-HEVs) exhibit significant engine torque fluctuations due to their mechanical coupling with the driveline, leading to pronounced torsional vibration issues in the drive shaft. This study investigates an active torsional vibration suppression strategy based on drive motor control. First, a dynamic model of the power-split-HEV driveline is established, and its intrinsic characteristics are analyzed. Subsequently, an engine excitation torque model is developed to identify the dominant response orders, while a vehicle dynamics model is constructed to elucidate the torsional vibration mechanisms in both hybrid and pure electric driving modes. Next, a torsional vibration feedback control framework is proposed, utilizing the electric motor as a secondary-channel torque disturbance compensator. Furthermore, a novel frequency-decoupled dual-loop control framework is proposed, with rigorous derivation of the sufficient conditions for decoupling. Based on this framework, two distinct vibration suppression algorithms are developed for the secondary-loop controller, each tailored for specific operational modes. Finally, the proposed algorithms are validated through simulation and hardware-in-the-loop (HIL) testing. The results demonstrate a torque fluctuation suppression ratio of up to 72.2%, confirming that the active suppression algorithm effectively mitigates driveline torsional vibration induced by engine harmonic torque disturbances.

The electromechanical transmission (EMT) systems of hybrid special vehicles are highly susceptible to severe transient torsional resonance under frequent start-stop operating conditions. Traditional entire-frequency domain H_∞ active vibration reduction strategies are often limited by insufficient gain, failing to achieve ultimate suppression within the core resonance frequency band. To address this issue, this paper proposes a finite-frequency H_∞ active torsional vibration suppression strategy based on a motor dual-loop control architecture. This strategy achieves a profound physical decoupling between torsional vibration suppression and steady-state driving tasks. Furthermore, by introducing the Generalized Kalman–Yakubovich–Popov (GKYP) lemma and Linear Matrix Inequalities (LMIs) into the secondary loop, the control degrees of freedom are precisely concentrated on the 8–30 Hz frequency band, where the transient resonance energy is highly localized. This thoroughly eliminates the conservatism inherent in entire-frequency designs. To mitigate the instability risks caused by unmeasurable states and actuator response lags in practical engineering applications, a robust controller integrating input time-delay compensation and dynamic output feedback is subsequently constructed. Numerical case studies and hardware-in-the-loop (HIL) test results based on a specific EMT configuration demonstrate that the proposed strategy effectively overcomes the instability induced by system delays. It achieves an outstanding resonance peak attenuation of up to 93% and strictly constrains output shaft torque fluctuations within a safe threshold of 50 N·m. Ultimately, this study provides an efficient and robust closed-loop engineering solution for the transient vibration management of high-power electromechanical transmission systems and the enhancement of overall vehicle NVH performance.