CAJ | 학술논문

为了满足量产车辆的自动变速器控制单元（transmission control unit，TCU）软件需求，研究了离合器换挡控制参数自整定控制方法，对自整定控制软件的结构和控制框图进行了介绍。针对换挡过程中，速度阶段和转矩阶段的特点，区别于传统方法对压力传感器、纵向加速度传感器和发动机转矩精度的依赖，分别提出了基于换挡时间的有动力升挡和基于涡轮失速问题的有动力降挡自整定策略。在实车测试过程中，通过软件的自整定参数调整，学习后的换挡时间能够逐步逼近设定的目标值，同时发动机飞车、涡轮失速现象能够逐步消减，换挡品质得到明显提升，保证了不同整车、不同发动机、不同变速器集成之后的换挡品质一致性，以及整车在产品生命周期内的驾驶性能一致性。实车采用该控制方法，在若干次相同工况的重复驾驶后，冲击点能明显弱化直至消除，冲击度逐步消减到低于5 m/s3，达到量产车辆水平，满足了某自主品牌车型投放上市要求。该研究对自动变速器换挡控制参数自整定策略研究和软件开发提供了参考。
위료만족양산차량적자동변속기공제단원（transmission control unit，TCU）연건수구，연구료리합기환당공제삼수자정정공제방법，대자정정공제연건적결구화공제광도진행료개소。침대환당과정중，속도계단화전구계단적특점，구별우전통방법대압력전감기、종향가속도전감기화발동궤전구정도적의뢰，분별제출료기우환당시간적유동력승당화기우와륜실속문제적유동력강당자정정책략。재실차측시과정중，통과연건적자정정삼수조정，학습후적환당시간능구축보핍근설정적목표치，동시발동궤비차、와륜실속현상능구축보소감，환당품질득도명현제승，보증료불동정차、불동발동궤、불동변속기집성지후적환당품질일치성，이급정차재산품생명주기내적가사성능일치성。실차채용해공제방법，재약간차상동공황적중복가사후，충격점능명현약화직지소제，충격도축보소감도저우5 m/s3，체도양산차량수평，만족료모자주품패차형투방상시요구。해연구대자동변속기환당공제삼수자정정책략연구화연건개발제공료삼고。
Adaption control strategy is a core technology as one part of control software for automatic transmission. The purpose of such strategy development is to compensate deviations due to engine torque signal difference, tolerance of transmission parts during manufacture, purchasing, storage and assembly processes, characteristics change with mileage accumulation, and to ensure acceptable shift quality and good drivability for the whole life of products. Many efforts have been made aimed to design self-learning strategies especially for dual-clutch automatic transmission and automated mechanical transmission by establishing vehicle launch strategy, feedback pressure control and solenoid duty cycle adjustment. While due to lack of pressure sensors in hydraulic automatic transmission, most of theories cannot be used directly. In overseas, main introductions on adaptive methods for upshift and downshift are published, but key technical information is strictly protected by corresponding patents and no detailed knowledge for instance control procedure is issued. According to different shift phases such as filling phase, torque phase and speeding phase, separated adaption methods like self-learning approach based on torque estimation or turbine acceleration signal are analyzed. But pressure sensor signal, longitudinal acceleration signal or high engine torque resolution are required for the application of those strategies, which seems not suitable for series transmission or low-level vehicles with domestic brands. To meet the requirements for TCU (transmission control unit) control software of vehicle production, adaption function for shifting clutches is researched, and corresponding software structure is introduced which includes shift type decision, shift quality monitoring, parameter adjustment and complicated method for adaption data update and storage. In addition, according to different profiles in torque phase and speeding phase for power on upshift and power on downshift, adaption strategies based on shifting time and turbine speed flare issue are proposed respectively. Then, according to shift sequence and shift control parameter of self-learning approach, complete software control procedures for parameter detection, processing, calculation and response are illustrated. It is very helpful for further research since parameter self-adjustment procedure turns to be clear with step by step introduction. A patent testing method is produced for recording shift issues, shift points, driving cycles and checking adaption results. The vehicle testing results showed that through adaption parameter adjustment, shifting time achieves to the target value, 700 ms, during power on upshift with only 2 repeated operations and for power on downshift, engine and turbine speed flare can be avoided gradually which makes shift quality better and more solid. The shift shock is reduced to 5 m/s3, which achieves to production vehicle shift quality level. The deviations due to the inconsistence of transmission from vehicle to vehicle and from engine to engine during manufacture and assembly process and characteristics deterioration can be compensated in very short time according to current research outcomes.