Mass flow estimation with model bias correction for a turbocharged Diesel engine

A systematic design method for mass flow estimation with correction for model bias is proposed. Based on an augmented observable Mean Value Engine Model (MVEM) of a turbocharged Diesel engine, the online estimation of states with additional biases is performed to compute the mass flows for different places. A correction method is applied, that utilizes estimated biases which are in a least-square sense redistributed between the correction terms to the uncertain mass flow maps and then added to the estimated mass flows. An Extended Kalman Filter (EKF) is tested off-line on production car engine data where the combination of an intake manifold pressure sensor, exhaust manifold pressure sensor and turbocharger speed sensor is compared and discussed in different sensor fusions. It is shown that the correction method improves the uncorrected estimated air mass flow which is validated against the airflow data measured in the intake duct.     

汽油机非线性卡尔曼滤波暂态进气量估计及空燃比控制

暂态工况下缸进气量的准确估计是提高发动机空燃比控制精度的有效措施之一,为此本文提出一种基于无迹卡尔曼滤波的暂态缸进气量估计算法,并利用估计的缸进气量设计了一种前馈-反馈空燃比控制器.MATLAB环境下的仿真实验给出了所提出的算法与现有进气量估计算法的比较,同时基于暂态气量估计的空燃比控制仿真实验验证了估计的有效性.论文与现有成果的区别在于:一是暂态进气量估计模型不仅包含了歧管压力动态还考虑了曲轴角速度动态,并采用了基于非线性辨识的均值模型;二是考虑了泵气波动的影响,采用了移动平均值法的数字滤波器对泵气波动进行滤波;三是采用无迹卡尔曼滤波算法对歧管压力和曲轴角速度进行估计.     

基于观测器的发动机转矩跟踪模型预测控制

针对如何实现发动机转矩快速精准地跟踪期望转矩的问题,提出一种基于观测器的模型预测控制策略.首先,利用均值模型对汽油发动机的进气歧管压力动态、转矩和转速动态进行建模,考虑到发动机真实转矩不可测的情况,采用Lyapunov稳定性理论和可测转速信号设计观测器对进气歧管压力进行在线估计,进而获得发动机的实时估计转矩;然后,利用基于观测器的模型预测控制算法设计转矩跟踪控制器,通过C/GMRES数值优化算法在线求解滚动时域优化问题,实现转矩的实时跟踪控制;最后,利用汽油发动机实验台进行实验验证以表明所提出算法的有效性.     

Modeling and online parameter estimation of intake manifold in gasoline engines using sliding mode observer

Model based control of automotive engines for fuel economy and pollution minimization depends on accuracy of models used. A number of mathematical models of automotive engine processes are available for this purpose but critical model parameters are difficult to obtain and generalize. This paper presents a novel method of online estimation of discharge coefficient of throttle body at the intake manifold of gasoline engines. The discharge coefficient is taken to be a varying parameter. Air mass flow across the throttle body is a critical variable in maintaining a closer to stoichiometric air fuel ratio; which is necessary to minimize the pollution contents in exhaust gases. The estimation method is based on sliding mode technique. A classical first Sliding mode observer is designed to estimate intake manifold pressure and the model uncertainty arising from the uncertain and time varying discharge coefficient is compensated by the discontinuity/switching signal of sliding mode observer. This discontinuity is used to compute coefficient of discharge as a time varying signal. The discharge coefficient is used to tune/correct the intake manifold model to engine measurements. The resulting model shows a very good agreement with engine measurements in steady as well s transient state. The stability of the observer is shown by Lyapunov direct method and the validity of the online estimation is successfully demonstrated by experimental results. OBD-II (On Board Diagnostic revision II) based sensor data acquisition from the ECU (Electronic Control Unit) of a production model vehicle is used. The devised algorithm is simple enough to be designed and implemented in a production environment. The online estimation of parameter can also be used for engine fault diagnosis work.     

Nonlinear Observer-based Control Design and Experimental Validation for Gasoline Engines with Exhaust Gas Recirculation

This paper presents a nonlinear observer-based control design approach for gasoline engines equipped with exhaust gas recirculation (EGR) system. A mean value engine model is designed for control which includes both the intake manifold and exhaust manifold dynamic focused on gas mass flows. Then, the nonlinear feedback controller based on the developed model is designed for the state tracking control, and the stability of the close loop system is guaranteed by a constructed Lyapunov function. Since the exhaust manifold pressure is usually unmeasurable in the production engines, a nonlinear observer-based feedback controller is proposed by using standard sensors equipped on the engine, and the asymptotic stability of the both observer dynamic system and control dynamic system are guaranteed with Lyapunov design assisted by the detail analysis of the model. The experimental validations show that the observer-based nonlinear feedback controller is able to regulate the intake pressure and exhaust pressure state to the desired values during both the steady-state and transient conditions quickly by only using the standard sensors.     

Control-oriented model for integrated diesel engine and aftertreatment systems thermal management

In order to perform effective real-time active thermal management, control-oriented thermal models for the integrated Diesel engine and aftertreatment systems are required. The purpose of this study is to develop a control-oriented temperature dynamic model for a modern Diesel engine equipped with a complete set of aftertreatment systems including Diesel oxidation catalyst (DOC), Diesel particulate filter (DPF), and urea-based selective catalytic reduction (SCR) system. In specific, the influences of in-cylinder post injection (fuel injection rate and injection timing) on the temperature dynamics were investigated. Several engine experiments were conducted to validate the proposed model in various operating scenarios. Experimental results show that the developed model can well capture the thermal behaviors of the aftertreatment systems with and without post injections.     

涡轮增压汽油机气路预测模型的建立与预测控制

针对涡轮增压汽油机气路系统中节气门与废气旁通阀动力学耦合、机理建模复杂的问题, 本文提出基于神经网 络模型的气路系统预测控制方法,实现了节气门与废气旁通阀的协调控制. 首先, 针对涡轮增压汽油机气路系统map与 机理混合描述的特性, 利用系统的输入输出数据,采用反向传播神经网络(back propagation neural network, BPNN)训 练得到一个非线性气路模型; 其次, 基于泰勒展开式对预测模型进行线性化, 并对模型的精度进行了验证,进而利用该 模型预测系统的未来动态; 然后, 在考虑系统存在输入约束的条件下, 设计了一个线性模型预测控制器对节气门与废气 旁通阀进行协调控制, 实现了进气歧管压力和升压的跟踪控制进而满足发动机的扭矩需求; 最后, 通过离线仿真和基 于dSPACE的快速原型实验(rapid control prototyping, RCP)验证了控制系统的有效性和实时性.     

废气再循环–可变几何截面涡轮增压柴油发动机 燃气双环系统建模及协同控制

针对废气再循环(EGR)与可变几何截面涡轮增压(VGT)的柴油发动机,作者联合考虑其燃油动力转速调节回路与气体回路,提出了内外双环稳定动态反馈的控制策略.其中,内环回路是利用Lyapunov函数设计的控制器,控制燃油质量流量来跟踪柴油发动机转速;外环回路则设计EGR–VGT控制器,跟踪气体回路的进排气歧管压力及压气机空气质量流量,并克服了柴油发动机建模中的不稳定零动态问题.同时,研究了气体流量与EGR和VGT阀门开度之间的关系,通过设计流量开度转换模块实现了两者控制的转换.最后,通过专业发动机软件AMESim与仿真软件MATLAB/Simulink的联合仿真试验,验证了该控制策略对柴油发动机燃油动力转速调节与气体回路控制的有效性.     

Simple adaptive air-fuel ratio control of a port injection SI engine with a cylinder pressure sensor

The problem of air-fuel ratio(AFR) control of the port injection spark ignition(SI) engine is still of considerable importance because of stringent demands on emission control. In this paper, the static AFR calculation model based on in-cylinder pressure data and on the adaptive AFR control strategy is presented. The model utilises the intake manifold pressure, engine speed, total heat release, and the rapid burn angle, as input variables for the AFR computation. The combustion parameters, total heat release,and rapid burn angle, are calculated from in-cylinder pressure data. This proposed AFR model can be applied to the virtual lambda sensor for the feedback control system. In practical applications, simple adaptive control(SAC) is applied in conjunction with the AFR model for port-injected fuel control. The experimental results show that the proposed model can estimate the AFR, and the accuracy of the estimated value is applicable to the feedback control system. Additionally, the adaptive controller with the AFR model can be applied to regulate the AFR of the port injection SI engine.     

Combustion timing control of HCCI engine based on NNPC and Elman-NN model under complex conditions

Homogeneous Charge Compression Ignition (HCCI) combines the characteristics of gasoline engine and diesel engine with high thermal efficiency and low emissions. However, since there is no direct initiator of combustion, it is difficult to control the combustion timing in HCCI engines under complex working conditions. In this paper, Neural Network Predictive Control (NNPC) for combustion timing of the HCCI engine is designed and implemented. First, the black box model based on Elman neural network is designed and developed to estimate the combustion timing. The fuel equivalence ratio, intake valve closing timing, intake manifold temperature, intake manifold gas pressure, and engine speed are chosen as the system inputs. Then, a NNPC controller is designed to control combustion timing by controlling the intake valve closing timing. Simulation results show that the Elman neural network black box model is capable of estimating the HCCI engine combustion timing. In addition, regardless of whether the HCCI engine is in constant or complex condition, the designed NNPC controller is capable of keeping the combustion timing within the ideal range. In particular, under New European Driving Cycle (NEDC) working conditions, the maximum overshoot of the controller is 28.95% and the average error is 1.03 crank angle degree. It is concluded that the controller has good adaptability and robustness.     

An engine fault diagnosis system using intake manifold pressure signal and Wigner–Ville distribution technique

This paper proposed an engine fault diagnosis system based on intake manifold pressure signal and artificial neural network with the Wigner–Ville distribution technique. Traditionally, the engine diagnostic method depends on the experience of the technician, but some faults might be inaccurately judged by the technician’s experience when the engine is operating. In the present study, an engine platform diagnosis system using intake manifold pressure was developed. The algorithm of the proposed system consisted of Wigner–Ville distribution (WVD) for feature extraction and the neural network technique for fault classification. In previous work, the Wigner–Ville distribution was often used to analyze the non-stationary signal, because it provides a simple and clear energy spectrum diagram both in the time and frequency domains. This instantaneous energy diagram presented the magnitude of each engine fault under various operating conditions. The Wigner–Ville distribution extracts these features as database input to a neural network and the neural network is used to develop the training and testing modules. To prove the efficiency of the neural network, both the radial basis function neural network and generalized regression neural network are used and compared. The experimental results demonstrated the proposed system is effective and the performance is satisfactory.     

汽车发动机模型硬件在环仿真研究

由于对汽车发动机模型研究侧重面不同,其方法、复杂度和深度也各异。为保证模型的相对简单和有效性并适应控制和诊断需要,简化了气缸内的燃烧过程和机械系统动力学过程,并在MATALB／SIMULNK环境下建立了面向控制和诊断的发动机模型,主要包括：进气岐管子模型,气缸内气体压力子模型和机械系统动力学模型,并基于RT-LAB机群对所建模型进行了硬件在环仿真。     

An adaptive estimator of fuel film dynamics in the intake port of a spark ignition engine

In order to meet the limits imposed on automotive emissions, engine control systems are required to constrain air/fuel ratio (AFR) in a narrow band around the stoichiometric value, due to the strong decay of catalyst efficiency in case of rich or lean mixture. An adaptive estimator, based on an extended Kalman filter, is proposed for the fuel film dynamics in the intake port of a spark ignition engine. The observer is based on a two states mean value model which accounts for the impingement of the injected fuel on the manifold walls and the evaporation process. The observer has been tested on a set of experimental transient maneuvers, showing a good accuracy in predicting the AFR.     

基于Abaqus的汽油机进气歧管爆破强度分析

介绍汽油机进气歧管的网格处理方法、进气歧管的约束和载荷,在考虑塑料材料弹性的非线性的情况下,计算进气歧管在发动机回火造成的爆破压力下的应力分布.结果可为进气歧管的设计和优化方向提供参考.     

增程器用天然气发动机转速双闭环自适应控制

针对增程器用天然气发动机参数不确定,输出扭矩难以精确计算,存在未知干扰,且需要大范围调速等问题,设计发动机转速的双闭环自适应控制策略,并分析系统的稳定性.所提策略的外环为发动机转速环,控制器输出为目标进气压力,内环为进气歧管压力环,控制器输出为节气门开度.该策略结构简单,不需要知道发动机各个参数的具体值,抗干扰性能强,能够满足增程器发动机大范围调速的特点.分别在Matlab/Simulink平台和增程器台架上验证了所提策略的有效性和实用性.     

Model based approach to closed loop control of 1-D engine simulation models

1-D engine simulation models are widely used for the analysis and verification of air-path design concepts to assess performance and therefore determine suitable hardware. The transient response is a key driver in the selection process which in most cases requires closed loop control of the model to ensure operation within prescribed physical limits and tracking of reference signals. Since the controller effects the system performance a systematic procedure which achieves close-to-optimal performance is desired, if the full potential of a given hardware configuration is to be properly assessed. For this purpose a particular implementation of Model Predictive Control (MPC) based on a corresponding Mean Value Engine Model (MVEM) is reported here. The MVEM is linearised on-line at each operating point to allow for the formulation of quadratic programming (QP) problems, which are solved as the part of the proposed MPC algorithm. The MPC output is used to control a 1-D engine model. The closed loop performance of such a system is benchmarked against the solution of a related optimal control problem (OCP). The system is also tested for operation at high altitude conditions to demonstrate the ability of the controller to respect specified physical constraints. As an example this study is focused on the transient response of a light-duty automotive Diesel engine. For the cases examined the proposed controller design gives a more systematic procedure than other ad hoc approaches that require considerable tuning effort.     

Two-degree-of-freedom H-infinity control of combustion in diesel engine using a discrete dynamics model

This paper proposes an H-infinity combustion control method for diesel engines. The plant model is the discrete dynamics model developed by Yasuda et al., which is implementable on a real engine control unit. We introduce a two-degree-of-freedom control scheme with a feedback controller and a feedforward controller. This scheme achieves both good feedback properties, such as disturbance suppression and robust stability, and a good transient response. The feedforward controller is designed by taking the inverse of the static plant model, and the feedback controller is designed by the H-infinity control method, which reduces the effect of the trubocharger lag. The effectiveness of the proposed method is evaluated in simulations using the nonlinear discrete dynamics model.     

Control of diesel engine dual-loop EGR air-path systems by a singular perturbation method

This paper presents a singular perturbation based method for controlling the dual-loop exhaust gas recirculation (DL-EGR) air-path systems on advanced diesel engines. A DL-EGR air-path system, consisting of a high-pressure loop EGR (HPL-EGR) and a low-pressure loop EGR (LPL-EGR), has significantly different time-scales (fast and slow) due to the inherent difference in the HPL-EGR’s and LPL-EGR’s corresponding control volumes. Such a feature of the DL-EGR systems makes the cooperative control of intake manifold gas conditions challenging. By considering the DL-EGR air-path system as a singularly perturbed system, a composite control law was devised to achieve systematic control of the air-path conditions including gas pressure, temperature, and oxygen fraction in the intake manifold. The effectiveness of the control method is experimentally evaluated on a medium-duty diesel engine.     

Gain-scheduling control of port-fuel-injection processes

An event-based sampled discrete-time linear system representing a port-fuel-injection process based on wall-wetting dynamics is obtained and formulated as a linear parameter varying (LPV) system. The system parameters used in the engine fuel system model are engine speed, temperature, and load. These system parameters can be measured in real-time through physical or virtual sensors. A gain-scheduling controller for the obtained LPV system is then designed based on the numerically efficient convex optimization or linear matrix inequality (LMI) technique. Simulation results show the effectiveness of the proposed scheme.     

Quantitative feedback design of air and boost pressure control system for turbocharged diesel engines

For modern diesel engines, variable geometry turbocharger (VGT) is used to boost engine power output. In addition, exhaust gas recirculation (EGR) is utilized to reduce engine out NO_x emission. To realize these functions, a multivariable control system needs to control both VGT and EGR valve to deliver desired intake manifold (or boost) pressure, and desired EGR flow rate. This two-input and two-output system is nonlinear with cross-couplings between the boost and EGR responses to the input actuators, the system parameters are varying with different engine operating conditions. This paper proposes a closed loop design of a multivariable VGT/EGR control system for a turbocharged diesel engine. The control system is synthesized based on quantitative feedback theory to maintain robust stability and performance via sequential MIMO loop shaping in the frequency domain. Experiment results are included from a turbocharged diesel engine to show the effectiveness of the proposed control design.