Simulation of a powertrain system for the diesel hybrid electric bus

The plug-in hybrid electric bus (HEB) is designed to overcome the vulnerable driving range and performance limitations of a purely electric vehicle (EV) and have an improved fuel economy and lower exhaust emissions than those of a conventional bus and convention HEBs. The control strategy of the plug-in parallel HEB??s complicated connected propulsion system is one of the most significant factors for achieving a higher fuel economy and lower exhaust emissions than those of the HEV. The proposed powertrain control strategy has flexibility in adapting to the battery??s state of charge (SOC), exhaust emissions, classified driving patterns, driving conditions, and engine temperature. Simulation is required to model hybrid powertrain systems and test and develop powertrain control strategies for the plug-in parallel HEB. This paper describes the simulation analysis tools, powertrain components?? models and modifications, simulation procedure, and simulation results.     

New level of vehicle comfort and vehicle stability via utilisation of the suspensions anti-dive and anti-squat geometry

In this article a novel vehicle dynamics control concept is designed for a vehicle equipped with wheel individual electric traction machines, electronically controlled brakes and semi-active suspensions. The suspension's cross-couplings between traction forces and vertical forces via anti-dive and anti-squat geometry is utilised in the control concept to improve driving comfort and driving stability. The control concept is divided into one main and two cascaded branches. The main controller consists of a multivariable vehicle dynamics controller and a control allocation scheme to improve the vehicle's driving comfort. The cascaded feedback loops maintain the vehicle's stability according to wheel slip and vehicle sideslip. The performance of the combined vehicle dynamics controller is compared to a standard approach in simulation. It can be stated that the controller piloting semi-active suspensions together with brake and traction devices enables a superior performance regarding comfort and stability.     

A stochastic quarter-car model for dynamic analysis of vehicles with uncertain parameters

A quarter-car model is used to investigate the vibration response of cars with uncertainty under random road input excitations in this paper. The sprung mass, unsprung mass, suspension damping, suspension stiffness, and tyre stiffness are considered as random variables. The road irregularity is considered a Gaussian random process and modelled by means of a simple exponential power spectral density. The power spectral density, mean value, standard deviation, and variation coefficient of the vehicle's natural frequencies and mode shapes are obtained by using the Monte Carlo simulation method. The computational expressions for the numerical characteristics of the mean square value of the vehicle's random response in the frequency domain are developed by means of the random variable's functional moment method. The influences of the randomness of the vehicle's parameters on the vehicle's dynamic response are investigated in detail using a practical example, and some useful conclusions are obtained.     

矿用无人运输车辆轨迹跟踪控制算法研究

矿用无人运输车辆作业环境恶劣,存在大曲率弯道、坡道等非结构化道路明显特征,对无人化运输控制要求高。为改善PID等传统控制算法适应性问题,提高无人驾驶轨迹跟踪的车辆横纵向控制精度,提出一种纯跟踪与PID结合的多点预瞄横向控制、考虑模糊控制表参数拟合的纵向控制方法,减少控制参数的同时提高算法效果。根据传统控制算法设计基础控制器,结合基础算法优势进行横向与纵向控制算法设计,通过硬件在环仿真和实车测试验证算法的性能。试验结果表明,横向控制算法与斯坦利算法相比,车辆路径跟踪精度有明显改善,纵向控制方面,速度跟随误差<1 km/h,保证了车辆驾驶时的平稳性与舒适性。     

车路协同条件下智能网联汽车一体化决策模型

为了探索当前有限数据条件下面临的无限交通场景问题,提出车路协同条件下基于深度强化学习智能网联汽车决策模型。利用Actor-Critic机制,以highway-env为数据来源,抽取144 h交通数据作为训练数据并进行验证,分析了智能网联汽车在不同车道数条件下的驾驶行为。结果显示,本模型汽车行程时间减少20%以上,碰撞概率减少25%以上,换道轨迹可以通过动力学跟踪。     

面向全矢量线控车辆极限运动的分层式协同控制

装配四轮分布式驱动-转向（4WID-4WIS）底盘的全矢量线控车辆具备多可控自由度、高速稳定性强的特点,是极限工况稳定裕度和安全性较高的理想车型。为了解决全矢量线控车辆在极限工况下纵横向控制冲突危害行车安全的问题,提出一种基于模型预测控制 （MPC） 的分层式车辆纵向和横向运动协同控制方法。建立基于单轨模型的期望运动状态识别方法,设计模型预测控制器转换动力学目标,采用泰勒展开和前向欧拉方法对预测模型进行线性离散化处理;设计基于负荷率的轮胎力优化分配方法,利用反正切轮胎逆模型求解控制执行量。仿真结果表明,协同控制方法能显著提高车辆在不同路面下的极限运动稳定性,更精准地跟踪期望运动状态,扩大稳定裕度,保障行车安全。     

A comprehensive study on the stability analysis of vehicle dynamics with pure/combined-slip tyre models

In this paper, a vehicle's lateral dynamic model is developed based on the pure and the combined-slip LuGre tyre models. Conventional vehicle's lateral dynamic methods derive handling models utilising linear tyres and pure-slip assumptions. The current article proposes a general lateral dynamic model, which takes the linear and nonlinear behaviours of the tyre into account using the pure and combined-slip assumptions separately. The developed methodology also incorporates various normal loads at each corner and provides a proper tyre–vehicle platform for control and estimation applications. Steady-state and transient LuGre models are also used in the model development and their responses are compared in different driving scenarios. Considering the fact that the vehicle dynamics is time-varying, the stability of the suggested time-varying model is investigated using an affine quadratic stability approach, and a novel approach to define the critical longitudinal speed is suggested and compared with that of conventional lateral stability methods. Simulations have been conducted and the results are used to validate the proposed method.     

匝道合流交通场景下自动驾驶汽车安全性测试评价方法

矿用无人运输车辆作业环境恶劣,存在大曲率弯道、坡道等非结构化道路明显特征,对无人化运输控制要求高。为改善PID等传统控制算法适应性问题,提高无人驾驶轨迹跟踪的车辆横纵向控制精度,提出一种纯跟踪与PID结合的多点预瞄横向控制、考虑模糊控制表参数拟合的纵向控制方法,减少控制参数的同时提高算法效果。根据传统控制算法设计基础控制器,结合基础算法优势进行横向与纵向控制算法设计,通过硬件在环仿真和实车测试验证算法的性能。试验结果表明,横向控制算法与斯坦利算法相比,车辆路径跟踪精度有明显改善,纵向控制方面,速度跟随误差<1 km/h,保证了车辆驾驶时的平稳性与舒适性。     

Modeling Human Vehicle Driving by Model Predictive Online Optimization

A driver model is designed which relates the driver's action to his perception, driving experience, and preferences over a wide range of possible traffic situations. The basic idea behind the work is that the human uses his sensory perception and his expert knowledge to predict the vehicle's future behavior for the next few seconds (prediction model). At a certain sampling rate the vehicle's future motion is optimized using this prediction model, in order to meet certain objectives. The human tries to follow this optimal behavior using a compensatory controller. Based on this hypothesis, human vehicle driving is modeled by a hierarchical controller. A repetitive nonlinear optimization is employed to plan the vehicle's future motion (trajectory planning task), using an SQP algorithm. This is combined with a PID tracking control to minimize its deviations. The trajectory planning scheme is experimentally verified for undisturbed driving situations employing various objectives, namely ride comfort, lane keeping, and minimized speed variation. The driver model is then applied to study path planning during curve negotiation under various preferences. A highly dynamic avoidance maneuver (standardized ISO double lane change) is then simulated to investigate the overall stability of the closed loop vehicle/driver system.     

Vehicle Modelling Aspects for an Embedded Real-Time Application

SUMMARY

In this paper we present results obtained for a driving advice system developed, within the framework of the Prometheus program. The main results concern the vehicle modelling, which is required for the evaluation of the vehicle's dynamic behaviour in real-time, and the safety parameters considered and developed in order to evaluate the vehicle's safety state. The demonstrator is briefly presented, together with the results.     

Economic value and utility of a powertrain system for a plug-in parallel diesel hybrid electric bus

This research is the first to develop a design for a powertain system of a plug-in parallel diesel hybrid electric bus equipped with a continuously variable transmission (CVT) and presents a new design paradigm of the plug-in hybrid electric bus (HEB). The criteria and method for selecting and sizing powertrain components equipped in the plug-in HEB are presented. The plug-in HEB is designed to overcome the vulnerable limitations of driving range and performance of a purely electric vehicle (EV) and to improve fuel economy and exhaust emissions of conventional bus and conventional HEBs. The control strategy of the complicated connected propulsion system in the plug-in parallel HEB is one of the most significant factors in achieving higher fuel economy and lower exhaust emissions of the HEV. In this research, a new optimal control strategy concept is proposed against existing rule-based control strategies. The optimal powertrain control strategy is obtained through two steps of optimizations: tradeoff optimization for emission control and energy flow optimization based on the instantaneous optimization technique. The proposed powertrain control strategy has the flexibility to adapt to battery SOC, exhaust emission amount, classified driving pattern, driving condition, and engine temperature. The objective of the optimal control strategy is to optimize the fuel consumption, electricity use, and exhaust emissions proper to the performance targets. The proposed control strategy was simulated to prove its validity by using analysis simulation tool ADVISOR (advanced vehicle simulator).     

Linear matrix inequality based control of vehicle active suspension system

Linear matrix inequality (LMI) methods, novel techniques in solving optimisation problems, were introduced as a unified approach for vehicle's active suspension system controller design. LMI methods were used to provide improved and computationally efficient controller design techniques. The active suspension problem was formulated as a standard convex optimisation problem involving LMI constraints that can be solved efficiently using recently developed interior point optimisation methods. An LMI based controller for a vehicle system was developed. The controller design process involved setting up an optimisation problem with matrix inequality constraints. These LMI constraints were derived for a vehicle suspension system. The resulting LMI controller was then tested on a quarter-car model using computer simulations. The LMI controller results were compared with an optimal PID controller design solution. The LMI controller was further tested by incorporating a nonlinear term in the vehicle's suspension model; the LMI's controller degraded response was enhanced by using gain-scheduling techniques. The LMI controller with gain-scheduling gave good results in spite of the unmodelled dynamics in the suspension system, which was triggered by large deflections due to off-road driving.     

Investigation of a passenger car's dynamic response due to a flywheel-based kinetic energy recovery system

With the advent of flywheel-based kinetic energy recovery systems in automotive applications new safety issues arise as a consequence of the flywheel's high rotational speed. While the special structural safety requirements of the components are well discussed in the literature, there is still little research on the influence of gyroscopic effects on vehicle dynamics. The aim of this paper is to investigate the influence of a typical high-speed flywheel on the driving dynamics of an average passenger car. To this end the equations of motion of a gyroscope are derived, which relate the vehicle's roll, pitch and yaw rate with the transverse torque acting on the flywheel. These equations are implemented in a commercial vehicle dynamics simulation program in order to determine the reaction torques acting on the vehicle within a representative range of driving situations. Numerical simulations indicate that the gyroscopic effect can be considered insignificant in standard driving situations.     

基于能量转移理论的行车风险量化建模方法研究

为建立一种简洁且适用的行车风险量化模型，提出了基于能量转移理论的行车风险量化建模方法，分析了换道避险场景和典型跟车场景的行车风险分布。模型从描述事故致因的能量转移理论出发，提出描述行车风险的风险作用力，通过考虑车辆的动力学约束，推导了车辆可行驶区域，明确了行车风险的影响范围，实现对风险分布的有效约束。仿真结果表明，模型能有效量化行车风险并与传统风险评估指标 THW的结果一致，同时，为缓解道路交通风险应当避免行车风险的大规模叠加造成的风险累积。     

Motion cueing in high-performance vehicle simulators

The majority of motion cueing algorithms have been developed for passenger car applications, with correspondingly less research dedicated to race-car and high-performance vehicle simulators. In the high-performance context, the focus is on cueing the vehicle's behavioural and handling characteristics, particularly when driving near the limits of performance. In race-car simulators the cueing requirements are therefore quite different, with the problem made all the more challenging by the presence of large accelerations. To understand the drivers' cueing needs, the vehicle's stability and handling response characteristics must be examined near the performance boundary. Frozen-time eigenvalue analyses are used to determine stability and response characteristics across all vehicle operating conditions, including accelerating and braking under cornering, with the results used to determine motion cueing algorithm requirements. Lateral acceleration and yaw cueing filters are designed in order to retain information critical to understanding the vehicle's behaviour on its performance boundary. Cueing filters are then tested, with the help of a professional race-car driver, and are found to provide the cues necessary for the driver to control the vehicle on the limit of performance.     

某柴油机SCR系统CFD仿真分析

排放法规的日趋严格,柴油机尾气后处理器SCR作为处理NOX排放物的一种有效手段,吸引了越来越多的目光的关注。柴油机尾气后处理器SCR内部的气体流动状况及尿素喷射效果与其使用效率以及柴油机的动力性和经济性都有很大的影响。文章通过建立三维SCR流动和喷雾计算模型,计算得出SCR内部压力、流场分布以及尿素喷射雾化分布情况。通过本次仿真,找到内部影响SCR工作效率的关键设计因素,从而更好的优化产品设计,满足性能及一致性的要求。结果表明:柴油机尾气后处理器SCR内部孔道的分布对于性能有一定的影响,需要通过生产进行控制从而满足尾气后处理的效率及产品一致性要求。     

基于深度强化学习与风险矫正的智能车辆决策研究

为实现高速公路环境下车辆的安全决策，提出一种结合深度强化学习和风险矫正方法的行为决策模型。构建决策模型所需的目标车辆及周围车辆的行驶信息，并引入自注意力安全机制，提高车辆在复杂高速场景下对周围潜在危险车辆的注意力，综合考虑行车效率、避障等因素以设计强化学习的奖励函数。此外，为解决强化学习在决策过程中缺乏安全性保障的问题，设计风险矫正模块对决策动作进行风险评估和矫正，避免危险决策的执行。在Highway-env仿真平台上对提出的决策模型进行训练和测试。试验结果表明，提出的决策模型有较高的行车安全率和鲁棒性，其驾驶效率也优于以规则、模仿学习和单纯深度强化学习为基础的决策方法。     

Estimation of the vehicle's centre of gravity based on a braking model

A vehicle's centre of gravity (CG) is an important property that affects the vehicle's handing stability, ride comfort and safety. For example, a high CG may lead to a serious traffic accident due to the adverse effects it may have on roll and handling stability. In this paper, we develop a dynamic detection method to obtain vehicle's height that uses a simulation model based on a dynamic analysis during braking. Simulations show that the dynamic detection method is feasible. Experiments with three different vehicles are performed to verify the proposed method. The previously established prediction detection and lifting detection (LD) methods are used for comparison. The experimental results demonstrate that the proposed method has higher accuracy and efficiency than the LD method. Thus, the proposed method is useful for the vehicle detection.     

基于动态门限值的分布式驱动电动汽车驱动力矩控制研究

为改善分布式驱动电动汽车高速行驶稳定性，避免频繁驱动控制操作对汽车行驶安全性的影响，提出了一种适应不同驾驶工况的参数动态门限值算法，设计了汽车附加横摆力矩滑模控制策略和驱动力矩二次规划优化分配控制策略，并进行了角阶跃输入工况和双正弦输入工况的仿真分析。结果表明，所设计的控制策略能有效控制汽车的质心侧偏角与横摆角速度，在保证汽车行驶稳定性的前提下，使质心侧偏角与理想值偏差减小了3.6%以上，轮胎附着利用率减少19.5%以上，有效地降低了轮胎附着利用率，提高了汽车的行驶安全性。     

Emission-robust operation of diesel HEV considering transient emissions

In this paper, we consider a method to create an engine emission simulation model for cycle and customer driving of a vehicle. The emission model results from an empiric approach, also taking into account the effects of engine dynamics on emissions. We analysed transient engine emissions in driving cycles and during representative customer driving profiles and created emission meta models. The analysis showed a significantly higher correlation in emissions when simulating realistic customer driving profiles using the created verified meta models (< 1 % model error) compared to static approaches, which are commonly used for vehicle simulation. Therefore, a transient modelling approach is conducted, which shows a great increase in accuracy in customer driving operation.