挡位离散型车辆经济性加速策略的伪谱法优化

加速过程中, 车辆的油耗与驾驶员的操作策略密切相关. 本文通过最优控制方法定量化地研究了挡位离散型车辆的经济性加速策略. 将加速策略的辨识构建为一个Bolza型最优控制问题(Optimal control problem, OCP), 设计了考虑加速距离影响的经济性定量评价指标. 该问题含有离散型控制变量, 隶属于混合整型最优控制问题, 且性能函数和状态方程呈现强非线性. 为高效地求解该问题, 结合变速器挡位切换规律, 将该整型问题转化为多段光滑问题的协同优化, 采用Legendre伪谱拼接法实现变速器挡位、换挡时机、发动机力矩的数值求解. 解析分析了经济性加速策略的形成机理, 总结了实用化的经济性加速度选择策略和挡位切换规律. 仿真验证了所求策略的节油潜力.     

Cognitive Work Analysis for safe and efficient driving

Both the environmental and safety costs of road transport are considered to be unacceptably high. The ‘Foot-LITE’ project aims to encourage drivers to adopt greener and safer driving practices, with real-time feedback being given in-vehicle (during driving) and retrospective feedback off-line (pre- and post-driving). This article focuses on the early concept development of the Foot-LITE system, for which a Cognitive Work Analysis methodology was adopted. Presented are results from a Work Domain Analysis (WDA) conducted to scope the relevant driving domain and to identify the constraints on the system. Besides establishing a common framework and language for the project, the process will ultimately contribute to the design of the in-vehicle interface. This article also suggests an extension to the WDA framework to include novel methods for assessing the priority of lower level nodes and contributions of these nodes to the high-level objectives of the system.     

利用通行能力余量的智能网联车队生态驾驶模型

针对非饱和城乡交通干道上存在通行能力余量和高燃油消耗的问题, 提出一种利用通行能力余量的智能网联车队生态驾驶模型, 该模型兼顾燃油经济性和通行能力两个目标, 通过优化求解获取最优速度曲线, 引导一系列小型车队平滑地通过非饱和城乡交通干道。提出近似的速度优化模型并采用遗传算法对其求解。定义3种控制方案对模型进行测试, 仿真结果表明: 与方案1相比, 方案2燃油消耗量减少49.4%, 通行能力增加200%, 绿灯剩余时间减少14.7%;方案3燃油消耗量减少59.5%, 通行能力增加200%, 绿灯剩余时间减少23.5%。与方案2相比, 方案3可以在不影响通行能力的前提下, 通过绿灯剩余时间缩短10.3%和平均速度降低5.2%, 燃油消耗量可以减少20%。结果表明, 当信号交叉口存在通行能力余量时, 可以通过调整车辆的行驶速度曲线以充分利用通行能力余量, 明显改善燃油经济性。     

基于Radau伪谱法和MPC的智能电动车辆生态驾驶

为优化智能电动车能源消耗,提出了基于Radau伪谱法和模型预测控制算法的智能电动车辆生态驾驶的方案。建立生态驾驶控制模型和能耗模型,结合边界约束和路径约束,构建生态驾驶能耗优化的最优控制问题。通过能耗优化得到最优车速轨迹,将此轨迹作为期望输入,基于模型预测控制( MPC)算法完成生态驾驶控制。实验结果表明：以纯电动车和实际规划路径为例,以最优车速自动行驶的能源消耗少于人工驾驶的能源消耗,验证了文中策略的有效性。     

Attitudes towards and perceptions of eco-driving and the role of feedback systems

This paper addresses whether eco-driving may be encouraged by providing drivers with feedback, and how eco-driving attitudes fit with other environmental attitudes. Eight focus groups, including fleet drivers, discussed how feedback and other motives might affect driving behaviour. A survey of 350 respondents investigated attitudes towards saving fuel, the role of incentives and use of eco-friendly products. The focus groups' findings show that the environment is a lower priority than comfort and convenience, that feedback might provide a stimulus to eco-driving and that saving money was less important than saving time. The attitude survey showed that price, convenience, attitudes and eco-driving are not conceptually linked together, that convenience is rated as more important than saving money from fuel efficiency and that although the environment is of concern, it is not a high enough priority to increase fuel efficiency. The findings are discussed in relation to the low level of priority given to environmental concerns and the inability of financial incentives presenting significant challenges in terms of changing the subjective norms of the majority of drivers.

Practitioner summary: This paper, using focus groups and a questionnaire, aims to understand how feedback devices, attitudes and motivation can improve eco-driving behaviours. The incentive to save money by better fuel economy was found to be insufficient, and roles for feedback devices and how information is presented are identified.     

Data mining for enhanced driving effectiveness: an eco-driving behaviour analysis model for better driving decisions

With the growing demand for energy efficient vehicles, automobile companies are constantly searching for better ways to study their customers’ driving behaviour for effective new product design and development. One emerging driving behaviour among modern, eco-friendly drivers is the utilising of advanced vehicle technology for smarter, safer and more fuel-efficient driving. While many eco-driving studies focus on minimising fuel consumption, little attention is paid to how the behaviour of an individual driver and the type of vehicle used impact driving effectiveness. This study addresses this gap by proposing a novel overall drive effectiveness index that uses data mining for better driving decisions. Utilising data mining techniques, the index examines the impact of driving behaviour on driving effectiveness. A novel fuel consumption prediction model based on vehicle speed, engine speed and engine load was constructed. This decision-making support model accurately predicts real-time fuel consumption based on different driving behaviours, and hence, the driving effectiveness. Both the proposed index and fuel consumption model can be used to support decision-making in new product design and development.     

基于驾驶模拟实验的生态驾驶行为节能减排潜力

针对生态驾驶行为在中国节能减排潜力尚不明确的问题,研究基于驾驶模拟实验平台,选取22名驾驶人进行生态驾驶行为培训和驾驶模拟实验测试,通过对比分析生态驾驶行为培训前和培训后的车辆能耗排放改善情况,确定生态驾驶行为的节能减排潜力.研究结果表明:生态驾驶行为节约汽车燃油消耗的潜力可达3.43%~5.45%;对应不同尾气排放物(CO₂、CO、HC和NO_x),生态驾驶行为的减排潜力可达3.39%~26.15%.随着培训强度的增加,生态驾驶行为所体现出的节能减排效益也相应增大.另外,职业和非职业司机驾驶行为节能减排潜力存在明显差异.     

CVT型车辆经济性加速策略优化与分析

不当的加速策略是造成车辆行驶油耗变差的重要原因,为降低加速过程油耗,通过伪谱最优控制方法定量化地研究CVT型车辆的经济性加速策略。在建立包含发动机油耗的车辆纵向动力学模型、提出消除加速距离影响的当量油耗指标基础上,将经济性加速策略的辨识构建为一个Bolza型最优控制问题。该问题的状态方程和性能指标具有强非线性,理论求解困难,因此利用Legendre伪谱法实现其数值求解,得到经济性加速度的量化表达,并进一步分析数值求解结果的形成机理。研究表明,经济性加速策略本质上是提高发动机效率和降低风阻能耗的整体协调优化;最优加速策略是与发动机特性和目标末速度密切相关的动态策略;过于激烈或平缓的加速度均会造成油耗变差。最后,仿真验证了经济性加速策略的潜在节油效果。     

A decision ladder analysis of eco-driving: the first step towards fuel-efficient driving behaviour

This paper provides a decision ladder analysis of eco-driving, and a discussion of the resultant models in terms of the skills, rules and knowledge taxonomy of human behaviour and how this can inform the design of an in-vehicle, eco-driving support system. In order to understand the types of behaviours that characterise fuel-efficient driving, a review was conducted of the academic literature and of more publicly available resources, such as governmental, car manufacturers' and specific eco-driving organisations' websites. The review identified four largely distinct driving activities that play a central role in the use of fuel in the private road vehicle. A focus group involving four researchers in the transport ergonomics field, followed by a series of five interviews with eco-driving experts, served to validate, supplement and further specify the models.

Practitioner Summary: This paper presents a decision ladder analysis of eco-driving. A four-member focus group and five interviews with eco-driving experts were conducted; the resultant models are discussed in terms of supporting fuel-efficient driving behaviours in the novice eco-driver through their potential to inform the design of an in-vehicle eco-driving support system.