Hybrid offline and online strategy for optimal high pressure seeking of the transcritical CO₂ heat pump system in an electric vehicle

The optimal discharge pressure corresponding to the highest coefficient of performance in a transcritical CO₂ heat pump system is influenced by several factors and is difficult to determine. This paper presents and implements a novel hybrid method connecting an improved offline part and an online part in series for optimal high-pressure seeking in a transcritical CO₂ heat pump system. Feedforward-feedback control is used to improve the dynamic characteristics of the offline part. The existence of the offline part decreases the gap between the final optimal value and initial value of the online part. The subsequent online part ensures the precision and robustness of the entire method. Different optimal high-pressure seeking methods are compared using a high-accuracy system model under various conditions. The results reveal that the hybrid method decreases the cabin temperature settling time by up to 34 and 807 s compared with the traditional offline and online methods, respectively. The long optimal pressure-seeking process of the traditional online method is shortened by 4934 s, and the corresponding average power consumption is reduced by 235 W between 0 and 5000 s by using the novel hybrid method. The novel hybrid method achieves a fast speed and high precision under different operating conditions, making the electric vehicle more comfortable and energy-efficient. The method can be optimized continuously by replacing offline or online parts with other advanced offline or online methods.