Optimal control strategy for vehicle starting coordination based on driver intention recognition

Xianhe Shang, Fujun Zhang, Zhenyu Zhang, Tao Cui
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Abstract

To enhance the starting performance of heavy-duty vehicles under different starting conditions, a vehicle starting coordinated optimal control method based on driver intention recognition is proposed. This method uses the Gaussian Mixture Model-Hidden Markov Model (GMM-HMM) for starting intention recognition, dividing the starting intentions into three categories: gentle start, normal start, and emergency start. The GMM-HMM starting intention recognition model is validated using real vehicle data. Based on the recognition results of driver intentions, a performance index function is defined as a weighted sum of smoke limit restriction time, 0–20 km/h acceleration time, and starting jerk. By assigning different weight coefficients, the allocation of requirements for starting power and comfort is achieved. Based on the principle of minimizing values, the coordinated control parameters (upshift speed and starting fuel quantity) are optimized, resulting in the optimal combination of coordinated control parameters under different starting intentions. This enables the optimal control of vehicle starting coordination based on the driver’s different starting intentions.
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基于驾驶员意图识别的车辆启动协调优化控制策略
为了提高重型车辆在不同起动条件下的起动性能,提出了一种基于驾驶员意图识别的车辆起动协调优化控制方法。该方法采用高斯混合模型-隐马尔可夫模型(GMM-HMM)进行起步意图识别,将起步意图分为三类:平缓起步、正常起步和紧急起步。GMM-HMM 启动意图识别模型使用真实车辆数据进行了验证。根据驾驶员意图的识别结果,定义了一个性能指标函数,该函数是烟度限制时间、0-20 km/h 加速时间和起步颠簸的加权和。通过分配不同的权重系数,实现了对起步动力和舒适性要求的分配。根据数值最小化原则,对协调控制参数(升挡速度和起步燃油量)进行优化,从而实现不同起步意图下协调控制参数的最优组合。这样就能根据驾驶员不同的起步意图对车辆起步协调进行优化控制。
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来源期刊
CiteScore
4.40
自引率
17.60%
发文量
263
审稿时长
3.5 months
期刊介绍: The Journal of Automobile Engineering is an established, high quality multi-disciplinary journal which publishes the very best peer-reviewed science and engineering in the field.
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