Permanent Magnet Synchronous Motors (PMSMs) have become widely adopted as the driving system in electric vehicles. Due to the harsh operating environment, model-free predictive control (MFPC) is implemented to enhance system robustness, resisting the negative influence caused by parameter mismatches. With the developing requirements of the driving experience, the necessity for inertia matching is highlighted, aiming to improve the dynamics and current ripples of the vehicles. 

A key limitation of traditional MFPC using ultra-local is its inability to adjust the system inertia according to the different operating states of the vehicles, thereby the realized driving performances and experiences are limited. 

In a study published in IEEE Transactions on Industry Applications, a research team led by Prof. WANG Fengxiang from Fujian Institute of Research on the Structure of Matter of the Chinese Academy of Sciences (CAS) designed an advanced adaptive inertia observer-based MFPC strategy in a PMSM driving system in the electric vehicle realm. 

The researchers introduced the implementing process of the typical ultra-local-based MFPC strategy under the continuous-control-set condition, in which all unknown terms of the plant are summarized as a single variable estimated by an extended state observer. Simplified the system as a group of transfer functions, an inertia ratio term is designed on the current reference signal, to make the system inertia adjustable. 

The researchers conducted a thorough analysis of the forces on the power wheel, to determine the current load torque under possible operating conditions, different loads, and road conditions of the vehicle. Based on a load torque estimation, its results are converted as the load inertia according to the proportional relationships on the force analysis. According to the inertia matching requirement, the system inertia is automatically selected as the minimum value within the suitable range, considering system dynamics and steady-state performances comprehensively. 

Besides, the researchers showed that this strategy gets good stability through the bode diagrams and pole/zero distributions, and analyzes the effects by the sampling periods. According to the experimental results, this strategy exhibits superior setting time and dropped depth within the transient-state, with a better sinusoidal degree in the phase current during the steady-state, compared with the traditional ultra-local-based MFPC. 

This study explores the potential of mitigating the effects of unsuitable system inertia for the vehicle’s load, culminating in an adaptive inertia observer that auto-satisfies the inertia matching requirement achieving better driving performances and experiences.  

Illustration of the Research(Image by Prof. WANG’s group) 

Contact:  

Prof. WANG Fengxiang 

Fujian Institute of Research on the Structure of Matter 

Chinese Academy of Sciences 

Email: fengxiang.wang@fjirsm.ac.cn