Despite the great progress of proton exchange membrane fuel cell (PEMFC) vehicle, the durability and cost of PEMFC still remain challenges. In this paper, a lifetime prediction model of PEMFC is developed by considering the platinum (Pt) electrochemical surface area (ECSA) degradation caused by steady power and transient power. The direct and continuous relationship between lifetime and real driving cycles is built by the proposed model. Firstly, the steady ECSA degradation model is deduced, and both the chemical and electrochemical dissolution of Pt particles are considered in the catalyst layer. The ECSA loss rate for steady power condition can be calculated by this model. Secondly, transient ECSA loss formula is obtained by fitting experimental data of PEMFC. This transient ECSA loss formula is used to calculate the ECSA loss rate under power changes condition. Thirdly, by applying the power voltage relationship, for a given power, the voltage can be calculated and applied to the two ECSA degradation models. Finally, the lifetime prediction method of PEMFC is proposed, and it is verified by PEMFC under three different driving cycles. Experimental test results show that the proposed lifetime prediction model accurately predict the lifetime of PEMFC under different driving cycles. The proposed method in this paper is more accurate compared with the method which divides the degradation into 4 conditions.

尽管质子交换膜燃料电池（PEMFC）车辆取得了长足的进步，但PEMFC的耐用性和成本仍然是挑战。本文通过考虑稳态功率和暂态功率引起的铂（Pt）电化学表面积（ECSA）退化，建立了PEMFC的寿命预测模型。寿命和实际驾驶周期之间的直接和连续关系是由提出的模型建立的。首先，推导了稳定的ECSA降解模型，并考虑了催化剂层中Pt颗粒的化学和电化学溶解。该模型可以计算出稳定功率条件下的ECSA损耗率。其次，通过拟合PEMFC的实验数据，得到瞬态ECSA损失公式。此瞬态ECSA损耗公式用于计算功率变化条件下的ECSA损耗率。第三，通过应用电源电压关系，对于给定的电源，可以计算电压并将其应用于两个ECSA退化模型。最后，提出了PEMFC的寿命预测方法，并通过PEMFC在三个不同的行驶周期下进行了验证。实验测试结果表明，提出的寿命预测模型可以准确预测PEMFC在不同行驶周期下的寿命。与将退化分为4个条件的方法相比，本文提出的方法更加准确。提出了PEMFC的寿命预测方法，并通过PEMFC在三个不同的行驶周期下进行了验证。实验测试结果表明，提出的寿命预测模型可以准确预测PEMFC在不同行驶周期下的寿命。与将退化分为4个条件的方法相比，本文提出的方法更加准确。提出了PEMFC的寿命预测方法，并通过PEMFC在三个不同的行驶周期下进行了验证。实验测试结果表明，提出的寿命预测模型可以准确预测PEMFC在不同行驶周期下的寿命。与将退化分为4个条件的方法相比，本文提出的方法更加准确。