Exhaust gas from series hybrid electric vehicle (SHEV) engines has characteristics different from those of conventional gasoline and parallel HEVs because there is a trend of iterated intermittent steady-state engine operation at a specific high-efficiency point and engine stop. A catalyst model that can reproduce the purification performance of a close-coupled three-way catalyst against the distinctive emissions of SHEVs was previously developed; however, improving the estimation accuracy in the period from a cold start to the completion of the light-off process remains challenging. To overcome this issue, the redox behavior of Rh was investigated in this study. After transient mode tests, the catalyst surface was oxidized due to exposure to high temperatures and an oxidative atmosphere for some time, causing activation deterioration. The activation promoted through light-off from the deteriorated state at cold start was modeled by introducing a rate equation with Arrhenius form to express the activation process. The completed model reproduced the performance trend in lean and rich iteration tests in a model gas experiment and achieved favorable estimation accuracy in worldwide light-duty test cycle mode calculation.

中文翻译：

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用于串联混合动力电动汽车的三元催化剂建模，重点关注冷启动时的催化行为

串联式混合动力汽车（SHEV）发动机的废气具有不同于传统汽油和并联式混合动力汽车的特性，因为在特定的高效点和发动机停止时，发动机存在迭代间歇性稳态运行的趋势。之前开发了一种催化剂模型，该模型可以再现紧密耦合的三元催化剂对 SHEV 独特排放的净化性能；然而，提高从冷启动到完成点火过程的估计精度仍然具有挑战性。为了克服这个问题，本研究研究了 Rh 的氧化还原行为。在瞬态模式测试后，催化剂表面由于暴露在高温和氧化气氛中一段时间​​而被氧化，导致活化劣化。通过引入具有 Arrhenius 形式的速率方程来表达激活过程，对冷启动时从劣化状态通过起燃促进的激活进行建模。完成的模型在模型气体实验中再现了贫富迭代测试的性能趋势，并在全球轻型测试循环模式计算中取得了良好的估计精度。