发动机高能直接点火控制技术设计

针对发动机电子点火系统的性能要求,以MC9S12DP256微控制器为核心,通过分析点火时序控制方法,设计点火控制程序,结合外围硬件设备,设计了六缸发动机高能直接点火系统。结果表明,利用MC9S12DP256微控制器的逻辑运算能力和定时控制功能,六缸发动机高能直接点火系统获得了精确、可靠的点火时序控制性能,使发动机电子点火系统获得了新发展。     

Engine Fault Analysis: Part II?Parameter Estimation Approach

The general fault analysis problem can be divided into two parts: fault detection and diagnosis (location). Fourier series, autocorrelation, and other techniques have been used for fault detection. However, these approaches cannot be utilized for locating the faults. In this paper a methodology is presented to locate faulty cylinder(s). The procedure involves the development of a mathematical model of the engine dynamics. This model takes into consideration the cylinder gas pressure, engine inertia, and load. The resultant torque is computed by using parameter estimation techniques. The parameter estimation technique employed can determine time-varying parameters without prior knowledge of the structure of the parameter. In the problem at hand, this is an important requirement. The resultant torque is the net of the cylinder gas torque and the frictional torque. The model and the estimation procedure have been verified by performing tests on a single-cylinder engine. A discriminant function has been defined to classify the performance of each cylinder. Our results indicate that the amplitude of the resultant torque can be used to identify the faulty cylinder(s). We have verified this approach by tests and studies on a six-cylinder engine. In our experiments we have studied cases involving one or two faulty cylinders.     

A neural-network based control solution to air-fuel ratio control for automotive fuel-injection systems

Maximization of the catalyst efficiency in automotive fuel-injection engines requires the design of accurate control systems to keep the air-to-fuel ratio at the optimal stoichiometric value AF/sub S/. Unfortunately, this task is complex since the air-to-fuel ratio is very sensitive to small perturbations of the engine parameters. Some mechanisms ruling the engine and the combustion process are in fact unknown and/or show hard nonlinearities. These difficulties limit the effectiveness of traditional control approaches. In this paper, we suggest a neural based solution to the air-to-fuel ratio control in fuel injection systems. An indirect control approach has been considered which requires a preliminary modeling of the engine dynamics. The model for the engine and the final controller are based on recurrent neural networks with external feedbacks. Requirements for feasible control actions and the static precision of control have been integrated in the controller design to guide learning toward an effective control solution.     

Design of computer controlled combustion engines

Globalization and growing new markets, as well as increasing emission and fuel consumption requirements, force the car manufacturers and their suppliers to develop new engine control strategies in shorter time periods. This can mainly be reached by development tools and an integrated hardware and software environment enabling rapid implementation and testing of advanced engine control algorithms.

The structure of a rapid control prototyping (RCP) system is explained, which allows fast measurement signal evaluation, and rapid prototyping of advanced engine control algorithms. A hardware-in-the-loop simulator for diesel engine control design is illustrated, simulation results for a 40 tons truck are presented. Providing efficient engine models for the proposed development tools, a dynamic local linear neural network approach is explained and applied for modelling the NO_x emission characteristics of a 1.9 l direct injection diesel engine. Furthermore the application of a RCP system is exemplified by the application of combustion pressure based closed-loop ignition timing control for a SI engine. Experimental results are shown for a 1.0 l SI engine on a dynamic engine test stand.     

面向众核密码处理器的高效负载均衡技术

工作负载分配不均是制约众核密码平台资源利用率提高的重要因素,动态负载分配可提高平台资源利用率,但具有一定开销;所以更高的负载均衡频率并不一定带来更高的负载均衡增益。因此,该文建立了关于负载均衡增益率与负载均衡频率的数学模型。基于模型,提出一种面向众核密码平台的无冲突负载均衡策略和一种基于硬件作业队列的“可扩展-可移植”负载均衡引擎——“簇间微网络-簇内环阵列”。实验证明:在性能、延时功耗积、资源利用率和负载均衡度方面,该文设计的负载均衡引擎与基于“作业窃取”的软件技术相比平均优化约4.06倍、7.17倍、23.01%和2.15倍;与基于“作业窃取”的硬件技术相比约优化1.75倍、2.45倍、10.2%、和1.41倍;与理想硬件技术相比,密码算法吞吐率平均只降低了约5.67%(最低3%)。实验结果表明该文技术具有良好的可扩展性和可移植性。     

自平衡机器人的机械建模与自平衡算法

针对高阶次、多变量、非线性、欠驱动的单轮机器人系统,提出了一种最优控制算法。首先采用机械方程推导出力学模型,通过将其在平衡位置处进行线性化,得到系统的线性化标称方程,然后用对称根轨迹（SRL）配置极点的控制方法实现了独轮机器人的动态稳定和平衡控制。仿真的结果验证了力学模型的正确性和反馈线性化控制算法的有效性。     

SVM-Based Approximate Model Control for Electronic Throttle Valve

An electronic throttle is a dc-motor-driven valve that regulates air inflow into the combustion system of an engine. The throttle control system should ensure fast and accurate reference tracking of the valve plate angle while preventing excessive wear of the throttle's components by constraining physical variables to their normal-operation domains. These high-quality control demands are hard to accomplish since the plant is burdened with the strong effects of stick–slip friction, a spring, and gear backlash. This paper proposes a support vector machine (SVM)-based approximate model control for the electronic throttle. The nonlinear control law is derived directly based on an input–output approximation method via the Taylor expansion, which avoids not only complex control development and intensive computation but also online learning or adjustment. Only a general SVM modeling technique is involved in both model identification and controller implementation. The robustness of the stability is established by the Lyapunov method. The proposed nonlinear controller is verified by computer simulations and experiments.      

Reference feedforward in the idle speed control of a direct-injection spark-ignition engine

The direct-injection spark-ignition engine has emerged as a focus of research in improving fuel economy and controlling emissions. This engine can operate in multiple modes, including a stratified charge mode with an air-fuel ratio as large as 50:1. Operating in stratified mode results in improved fuel economy and reduced CO/sub 2/ emissions. The stratified charge mode is employed during low speed and load conditions, such as during engine idle. The idle speed control problem is cast as a two-input-two-output control problem and a baseline feedback controller is developed based on an existing topology from the literature. Significant delays, however, inhibit our ability to improve the transient response via feedback alone. An improved scheme employing reference feedforward is proposed and several potential topologies are presented. A reference feedforward algorithm is derived and nonlinear simulation results are shown in which the system transient responses are improved considerably.     

A dynamic load balancing strategy for channel assignment using selective borrowing in cellular mobile environment

We propose a dynamic load balancing scheme for the channel assignment problem in a cellular mobile environment. As an underlying approach, we start with a fixed assignment scheme where each cell is initially allocated a set of channels, each to be assigned on demand to a user in the cell. A cell is classified as 'hot', if the degree of coldness of a cell (defined as the ratio of the number of available channels to the total number of channels for that cell), is less than or equal to some threshold value. Otherwise the cell is 'cold'. Our load balancing scheme proposes to migrate unused channels from underloaded cells to an overloaded one. This is achieved through borrowing a fixed number of channels from cold cells to a hot one according to a channel borrowing algorithm. A channel assignment strategy is also proposed based on dividing the users in a cell into three broad types – 'new', 'departing', 'others' – and forming different priority classes of channel demands from these three types of users. Assignment of the local and borrowed channels are performed according to the priority classes. Next, a Markov model for an individual cell is developed, where the state is determined by the number of occupied channels in the cell. The probability for a cell being hot and the call blocking probability in a hot cell are derived, and a method to estimate the value of the threshold is also given. Detailed simulation experiments are carried out in order to evaluate our proposed methodology. The performance of our load balancing scheme is compared with the fixed channel assignment, simple borrowing, and two existing strategies with load balancing (e.g., directed retry and CBWL), and a significant improvement of the system behavior is noted in all cases. This revised version was published online in June 2006 with corrections to the Cover Date.     

基于模糊控制的启发式工作流引擎负载均衡策略

针对分布式工作流引擎中的负载均衡问题,提出了一种新的算法,即启发式模糊算法,将传统控制理论中的模糊控制和启发式策略应用到了工作流负载均衡中。最后在一个基于JINI的分布式网络系统中实现了该算法,并且给出了其与其他几种经典算法进行比较的实验结果。结果表明,启发式模糊算法提高了工作流引擎服务的整体响应时间,使得资源得到了更加合理的利用。     

MPC of Switching in a Boost Converter Using a Hybrid State Model With a Sliding Mode Observer

In this paper, a model of a dc–dc (boost) converter is first expressed as a hybrid/switched/variable-structure system state model for the purpose of applying recently developed hybrid optimal control theory to control switching in a boost converter. Switching control is achieved by forming the embedded form of the hybrid state model, which enables the derivation of a control that solves for the switching function that minimizes a user-defined performance index. This approach eliminates the need to form average-value models and provides flexibility to balance competing objectives through appropriate weighting of individual terms in the performance index. Since, in practical situations, both the source voltage and the load resistance vary with time in unknown and unmeasurable ways, we introduce a sliding mode observer based on an enlarged state model which allows implicit estimation of the unknown variables. The combined optimal switching control and sliding mode observer are applied to a boost converter in which several nonidealities and losses are represented. The results of time-domain simulation and hardware experiments are used to validate and compare the response of the hybrid optimal control–sliding mode observer to that of a traditional current-mode control strategy.      

Dynamic Origin–Destination Flow Estimation Using Cellular Communication System

This paper aims to develop a new approach for the estimation of dynamic origin–destination (O–D) flow using cell phones as traffic probes. The state-space model, which depends on the autoregressive dynamics of O–D flow and the time series for link volume counts, was adopted. Unlike a direct approach that uses sample O–D flows extracted from the cell-based location data as additional observations, an indirect approach is proposed wherein the assignment map in the model is derived from the passing time at observation locations and the path choice proportion. A probe phone's passing time at a certain point in a cell was approximated with its entry and exit times at cell boundaries. The average path choice proportion was also estimated using cell-based trajectories of probe phones. The simulation experiments confirmed that the approach was successfully applicable to the real-world freeway network. The results suggest that the O–D flows estimated from the present approach are promising in that the mean absolute error ratio was smaller than the case wherein only historical O–D flows are concerned. A sensitivity analysis revealed that the present approach met the requirements for an urban area encompassing a huge number of cell phone users in a microcell system.      

Nonlinear air-to-fuel ratio and engine speed control for hybrid vehicles

Internal combustion spark ignition engine management systems regulate the fuel, spark, and idle air subsystems to achieve sufficient engine performance at acceptable fuel economy and tailpipe emission levels. Engine control units also monitor other engine processes, using a suite of sensors, and periodically check the system actuators' operation to satisfy legislated onboard diagnostics. The majority of production engines regulate the air-to-fuel ratio using a speed-density, or air-flow, control strategy. In this approach, the mass of air drawn into a given cylinder is calculated using the engine speed, manifold absolute pressure, and inlet air temperature. Based on the air mass, appropriate fuel amounts are injected to achieve stoichiometric operation. However, the wide range of operating conditions, inherent induction process nonlinearities, and gradual component degradations due to aging have prompted research into model-based algorithms. In this paper, a nonlinear model-based control strategy will be proposed for simultaneous air-to-fuel ratio control and speed tracking in hybrid electric vehicles. The motivation for engine speed management resides in the integrated control of the engine and a continuously variable transmission for increased efficiency. The proposed backstepping controller uses an observer to reduce the inputs to manifold air mass (e.g., manifold absolute pressure and inlet air temperature) and engine speed. The underlying engine model describes the air intake, fuel injection, and rotational dynamics. For comparison purposes, an existing multisurface sliding mode controller and an integrated speed-density air-to-fuel controller with attached engine speed regulation have been implemented. The performance of each controller is studied using an analytical engine model with representative numerical results presented and discussed to provide insight into the overall performances.     

A distributed implementation of mobility load balancing with power control and cell reselection in 4G network

We consider a self‐organizing network (SON) capability of mobility load balancing in a 4G network, which determines the transmission power level for individual base stations and cell reselection for individual mobile stations such that the network‐wide load is minimized while satisfying the minimum signal‐to‐noise and interference ratio (SINR) requirement of individual users. Both centralized and distributed schemes are proposed. The centralized scheme is based on the greedy algorithm, serving as a performance bound to the distributed scheme. The distributed scheme is to solve the system‐wide optimization problem in the flat network model, i.e. no central control node. Furthermore, it requires relatively low inter‐cell exchange information among neighboring cells over an inter‐cell channel, e.g. X2 interface in the LTE network. The proposed design objective is to minimize the number of mobile users that do not satisfy the specified average throughput, while distributing the user traffic load as uniformly as possible among the neighboring cells. Our simulation results for a uniform user distribution demonstrate that the proposed scheme can achieve up to almost 80% of a load balancing gain that has been achieved by a greedy algorithm in the centralized optimization. Copyright © 2014 John Wiley & Sons, Ltd.     

Enhancing Real-Time Delivery in Wireless Sensor Networks With Two-Hop Information

A two-hop neighborhood information-based routing protocol is proposed for real-time wireless sensor networks. The approach of mapping packet deadline to a velocity is adopted as that in SPEED; however, our routing decision is made based on the novel two-hop velocity integrated with energy balancing mechanism. Initiative drop control is embedded to enhance energy utilization efficiency, while reducing packet deadline miss ratio. Simulation and comparison show that the new protocol has led to lower packet deadline miss ratio and higher energy efficiency than two existing popular schemes. The result has also indicated a promising direction in supporting real-time quality-of-service for wireless sensor networks.     

基于算术编码的异构双核SoC代码压缩方法

介绍了一种基于二进制算术编码和马尔可夫模型的代码压缩算法,并以此为基础,面向自主研发的异构双核SoC—GEM-SOC,提出了一种软件实现的解码方法。该方法可以根据不同应用的代码特点,选择合适的马尔可夫模型参数,从而达到最佳的代码压缩率。一组媒体应用测试表明,该方法可以显著减小双核SoC中DSP处理器的代码尺寸。     

VGT turbocharger controlled by an adaptive technique

This paper provides an adaptive technique for the control of the variable geometry turbine in a turbocharged compression ignition engine. The adaptive control is based on a one-step-ahead (OSA) technique and a least-square parameter estimator algorithm. In order to test the performance of the proposed control technique, a numerical model of the engine has been developed, which employs a thermodynamic (zero-dimensional) approach. The paper will show that the OSA technique is able to improve dramatically the control performance with respect to that provided by a commonly applied proportional integral derivative control technique.     

Load balancing for cellular/WLAN integrated networks

The interworking between heterogeneous third-generation cellular networks and wireless local area networks is one promising evolution approach to fourth-generation wireless networks, which can exploit the complementary advantages of the cellular network and WLANs. Resource management for the 4G-oriented cellular/WLAN integrated network is an important open issue that deserves more research efforts. In this article we present a policy framework for resource management in a loosely coupled cellular/WLAN integrated network, where load balancing policies are designed to efficiently utilize the pooled resources of the network. A two-phase control strategy is adopted in the load balancing policies, in which call assignment is used to provide a statistical quality of service guarantee during the admission phase, and dynamic vertical handoff during the traffic service phase is used to minimize the performance variations. Numerical results are presented to demonstrate that the proposed load balancing solution achieves significant performance improvement over two other reference schemes     

An Approximate Calculation of Ratio of Normal Variables and Its Application in Analog Circuit Fault Diagnosis

The challenging tolerance problem in fault diagnosis of analog circuit remains unsolved. To diagnose the soft-fault with tolerance effectively, a novel diagnosis approach based on the ratio of normal variables and the slope fault model was proposed. Firstly, the approximate distribution function of the ratio of normal variables was deduced and the basic approximate conditions were given to improve the approximation accuracy. The conditional monotonous and continuous mapping between the ratio of normal variables and the standard normal variable was proved. Based on the aforementioned proved mapping, the estimation formulas of the range of the ratio of normal variables were deduced. Then, the principle of the slope fault model for linear analog circuit was presented. After the contrastive analysis of the typical methods of handling tolerance based on the slope fault model, the ratio of normal variables and the slope fault model were combined and a test-nodes selection algorithm based on the basic approximate conditions of ratio of normal variables was designed, by which the computation can be reduced greatly. Finally, experiments were done to illustrate the proposed approach and demonstrate its effectiveness.     

Sliding mode based powertrain control for efficiency improvement in series hybrid-electric vehicles

This study involves the improvement of overall efficiency in series hybrid-electric vehicles (SHEVs) by restricting the operation of the engine to the optimal efficiency region, using a control strategy based on two chattering-free sliding mode controllers (SMCs). One of the designed SMCs performs engine speed control, while the other controls the engine/generator torque, together achieving the engine operation in the optimal efficiency region of the torque-speed curve. The control strategy is designed for application on a SHEV converted from a standard high mobility multipurpose wheeled vehicle (HMMWV) and simulated by using the Matlab-based PNGV Systems Analysis Toolkit (PSAT). The performance of the control strategy is compared with that of the original PSAT model, which utilizes PI controllers, a feedforward term for the engine torque, and comprehensive maps for the engine, generator and power converter (static only), which constitute the auxiliary power unit (APU). In this study, in spite of the simple modeling approach taken to model the APU and the optimal efficiency region, an improved performance has been achieved with the new SMC based strategy in terms of overall efficiency, engine efficiency, fuel economy, and emissions. The control strategy developed in this work is the first known application of SMC to SHEVs, and offers a simple, effective and modular approach to problems related to SHEVs.