Overview of Chassis Domain Control System Architecture, Algorithms, and Verification Techniques

This paper discusses the model-based predictive controller design of networked nonlinear systems with communication delay and data loss. Based on the analysis of the closed-loop networked predictive control systems, the model-based networked predictive control strategy can compensate for communication delay and data loss in an active way. The designed model-based predictive controller can also guarantee the stability of the closed-loop networked system. The simulation results demonstrate the feasibility and efficacy of the proposed model-based predictive controller design scheme.

Integrating self-health awareness in autonomous systems

The synchronization of somatic motor outflow and sympathetic efferent activity during exercise has important functional consequences. For example, a certain degree of sympathetic vasoconstriction to active skeletal muscle vascular beds may be required to prevent an excessive decrease in vascular resistance during intense dynamic exercise involving a large skeletal muscle mass. Moreover, the redistribution of blood flow away from non-exercising vascular beds to contracting skeletal muscles is necessary to meet their increased metabolic demands. Historically, the nervous system has been separated arbitrarily into a volitional (somatic) and a reflex (autonomic) control system that does not necessitate volitional input (Koizumi & Brooks, 1972). However, during exercise this partition of the somatic and autonomic control systems is replaced by an overlapping control system that influences both somatic and sympathetic outflows in a parallel fashion. Previous work has suggested that the integration and co-ordination of the somatic and sympathetic motor responses during exercise were mediated by a supraspinal neural mechanism referred to as central command (Waldrop et al. 1996). However, there is an accumulating body of evidence, including papers on the role of the spinal cord in the regulation of sympathetic outflow (Weaver & Stein, 1989), suggesting that rhythmic neural activity destined for somatomotor and sympathetic outflows may be under the control of intrinsic neuronal circuitry in the spinal cord. In this issue of The Journal of Physiology, the paper by Chizh et al. (1998) demonstrates for the first time that some components of somatic motor and sympathetic neural outflows are synchronized by a spinal mechanism. The authors studied the relationship between sympathetic and somatic motor outflows from the thoraco-sacral spinal cord using an isolated trunk-hindquarters preparation of the adult mouse. They found that some of the activity in both somatic and sympathetic outflows was coupled. However, since there was also sympathetic neural activity that showed burst discharges in the absence of somatic motor activity, the spinal mechanism responsible for generating sympathetic burst activity was not the same mechanism that was responsible for somato-sympathetic coupling. Therefore, there remained spinal mechanisms that were capable of generating bursting activity independently of somatic and sympathetic activities. When NMDA was added to the perfusate to induce rhythmic somatic motor activity, a dose-dependent bursting pattern in sympathetic efferent and somatic motor nerves was evoked that was coupled at similar frequencies. Correlational analyses found a strong coherence between somatic motor outflow and sympathetic efferent discharge when triggered from peaks in somatic motor activity. However, this synchronization was not found when triggered from the peaks of sympathetic discharge. This finding led Chizh et al. (1998) to hypothesize that the generating mechanism responsible for somatic locomotor activity was the same mechanism responsible for coupling somatic outflow to sympathetic activity. These findings support the notion that the spinal cord possesses the necessary neuronal ‘machinery’ for generating and coupling sympathetic discharge with somatic motor outflow independently of supraspinal structures (i.e. the spinal rhythm generator represents a spinal central command). Important adjustments occur in the heart and blood vessels during exercise in order to provide the appropriate oxygen delivery to match the metabolic demand of contracting skeletal muscle. The coupling of somatic motor and sympathetic outflows is mediated by supraspinal neural mechanisms (supraspinal central command) in humans and animals (Fig. 1). In humans, intense intermittent static exercise produced a one-to-one synchronization of somatic motor activity with muscle sympathetic nerve activity that was purportedly directed to skeletal muscle vasculature (Victor et al. 1995). This synchronization persisted in the presence of both partial neuromuscular blockade (i.e. to increase central command) and after local anaesthetic block of the arm nerves to eliminate afferent feedback from skeletal muscle. Likewise, electrical and chemical stimulation of the hypothalamic locomotor region in decorticate cats after neuromuscular blockade evokes fictive locomotion that produces increases in arterial blood pressure (Waldrop et al. 1996) and synchronization of sympathetic nerve activity with hindlimb motor nerve activity (Hajduczok et al. 1991). And, as seen in humans, the synchronization of somatic motor activity and sympathetic discharge was unaffected by peripheral feedback mechanisms. These findings suggest that central command signals of supraspinal origin can regulate and co-ordinate sympathetic and somatomotor outflows during exercise. Figure 1 Synchronization of somatic motor outflow and sympathetic efferent activity during exercise is mediated by supraspinal and spinal mechanisms. The important work of Chizh et al. (1998) extends our understanding of the synchronization of somatic motor activity and sympathetic outflow by highlighting the role of a spinal somato-sympathetic generator (Fig. 1). Also, the coupling of somato-sympathetic neural outflows in the spinal cord may represent an exquisite mechanism to finely tune sympathetic discharge to the segmental level of somatic motor outflow during exercise. Finally, {fontsize the degree to which supraspinal central command signals influence the somato-sympathetic spinal generator needs to be studied to further our understanding of somato-sympathetic coupling during volitional exercise.

Integrated chassis control (ICC) systems are designed to coordinate the control actions of individual chassis control systems, in order to achieve superior overall control performance. Many existing ICC systems employ an implicit mechanism to allocate/distribute the global target control action between the subsystems, which may lead to contradictory or suboptimal individual control actions. To deal with this shortcoming, this paper proposes an ICC solution based on multi-input multi-output sliding mode control. The coupled dynamics between the vehicle states to be controlled are explicitly incorporated in the proposed control design, and the control actions of active rear steer (ARS) and direct yaw-moment control (DYC) are jointly determined by the controller rather than allocated or distributed from a global target control action. Simulink-CarSim co-simulation results show that the ARS and DYC subsystems are well coordinated by the proposed controller to achieve favorable vehicle responses, including side slip angle, yaw rate and vehicle path. under a challenging driving condition.

Modern automotive as a distinctive and enormous market is undergoing radical changes due to increasingly embedded electronics systems inside automobiles. These changes are considered as a new phase in the automotive industry, which enables automotives to be more intelligent and reliable. As witnessed in the automotive industry development in the last decade, electronic devices play a critical role in various automotive systems, such as in the power control system, chassis control system, security system, and even in the entertainment system; and indeed more than 70% of the technical innovations in automotives nowadays are due to electronics systems. In general, there are 4 main classifications in automotive electronics. namely, engine/powertrain, body/chassis, safey/security and telematics/entertainment, where keyless entry, tire pressure monitoring system (TPMS), air bag, collision avoidance and adaptive front-light systems are identified as the 5 most promising automotive electronics applications by Year 2010. To support the continuous development of automotive electronics, advanced packaging technology definitely represents one of the key enabling technologies. In tins paper we select TPMS as an example to demonstrate the role of advanced packaging in product evolutions requiring multiple functions within a confined space.

Global chassis control maximizes chassis control performance by integrating and controlling individual chassis control systems in an integrated and compensatory manner. A global chassis control system thus requires high reliability, even in case of failure or fault. The system should be capable of detecting failure under various conditions, and responding to failure appropriately to guarantee uninterrupted performance. In this paper, we propose a fail-safe strategy to improve reliability of the global chassis control system. We have implemented the global chassis control system in a way that a higher-level controller monitors driver intention and vehicle status, and then commands lower-level, chassis controllers to maximize vehicle performance. Depending on failure detection types of sensors and actuators in the control system, we developed different fail-safe methods: we combined actual hardware sensors and virtual algorithm sensors appropriately depending on whether other sensor signals can be used to determine failure of the sensor or not. Simulation results demonstrate effectiveness of the fail-safe strategy and improvement of system reliability

TEMIC TELEFUNKEN microelectronic GmbH (TEMIC), a subsidiary of AEG Daimler-Benz Industrie, runs manufacturing systems at different locations for the production of electronical parts for a variety of applications. TEMIC offers solutions to automobile manufacturers for passive and active safety elements, driving comfort and operator convenience, as well as systems for reducing fuel consumption and pollutant emission. TEMIC modules also control antilock brake and traction control systems. Numerous automobiles from leading manufacturers come with TEMIC engine and chassis control systems, as well as with comfort features like mirror and seat setting memories.

A novelGlobal Chassis Control(GCC) system based on a multilayer architecture with three levels: top: decision layer, middle: control layer, and bottom: system layer is presented. The main contribution of this work is the development of a data-based classification and coordination algorithm, into a single control problem. Based on a clustering technique, the decision layer classifies the current driving condition. Afterwards, heuristic rules are used to coordinate the performance of the considered vehicle subsystems (suspension, steering, and braking) using local controllers hosted in the control layer. The control allocation system uses fuzzy logic controllers. The performance of the proposed GCC system was evaluated under different standard tests. Simulation results illustrate the effectiveness of the proposed system compared to an uncontrolled vehicle and a vehicle with a noncoordinated control. The proposed system decreases by 14% the braking distance in the hard braking test with respect to the uncontrolled vehicle, the roll and yaw movements are reduced by 10% and 12%, respectively, in the Double Line Change test, and the oscillations caused by load transfer are reduced by 7% in a cornering situation.

<div class="htmlview paragraph">Chassis control systems, including ABS, traction control and vehicle stability control, utilize the available tire forces to improve vehicle acceleration, deceleration, handling and stability for active safety. Thus, it can be very beneficial to evaluate the tire force characteristics on actual road surfaces and use this information in the chassis control systems. In this paper, the research activities on evaluating the tire force characteristics and the performance of chassis control systems are introduced. The test procedure described for measuring the tire force characteristics on actual road surfaces using a test vehicle is relatively easy. The brake and side force characteristics are shown from the experimental data. The tire force characteristics during ABS braking were measured on various road surfaces. ABS performance is discussed based on the measured tire force characteristics. These test results illustrate a trade-off between vehicle deceleration and handling performance due to the ABS operating range from the view point of the tire force characteristics.</div>

With the development of vehicle intelligence and electrification, the performance of vehicle chassis system is highly demanded. Most existing researches have adopted the structure parameters optimization design method for the partial chassis subsystem, which cannot improve global vehicle performance. In this paper, the chassis system of distributed drive electric vehicles is taken as the research object. The chassis system integration optimization design method is studied. Firstly, the dynamic vehicle model, which includes active suspension, electric power steering, and motor braking systems, is established. Secondly, according to the performance requirements of suspension, the riding comfort index is formulated. According to the requirements of steering performance, the indexes of steering road feel and steering sensitivity are derived. According to the performance requirements of the braking system, the braking feel index is formulated. Based on the subsystem indexes, the comprehensive performance evaluation index of “comfortable-stability” of electric vehicle chassis system is proposed for the first time. Aiming at the minimum of the weighted sum of each subsystem performance index, the optimization constraints of the suspension, steering, and braking systems are considered. In order to avoid the subjectivity of weight selection, the weight coefficient of the optimization target is determined by the weight method of CRITIC. Then the chassis system’s mathematical model of multi-objective optimization is established. Finally, based on the NSGA-II algorithm, the chassis system is optimized. And based on the simulation software, the comparative analysis is carried out. Simulation results indicate that compared with the unoptimized vehicle, the amplitude of FVA and RVA indexes of the optimized vehicle is reduced by 9.87% and 2.23%, the amplitude of steering road feel index is increased by 15.51%, and the amplitude of BF index is reduced by 20.13%. The comprehensive performance of the vehicle chassis has been improved.

Model Based Predictive Control (MBPC) is a class of computer algorithms that explicitly use a process model to predict future plant outputs and compute an appropriate control action through on-line optimization of a cost objective function over a future horizon, subject to various constraints. This paper presents an MBPC type algorithm applied to nonlinear processes. The basic idea of the algorithm is the on-line simulation of the future behavior of the control system, by using a few candidate control sequences. Then, using rule based control, these simulations are used to obtain the `optimal' control signal. The efficiency and applicability of the proposed algorithm are demonstrated through applications.

Basic study for realization of adaptation, evolution, and self-diagnosis on an artificial heart has been carried out by an autonomous distributed control system for an ultra-lightweight pulsatile VAD (volume of 285 ml and weight of 360 g). The autonomous distributed control system was build by 4 layers (input layer, measurement layer, control layer, output layer) and an object manager, which was realized on a l chip microcomputer (Hitachi, SH7044, Japan). The input and output layer are composed of ND, PIO, SIO for interface with the VAD. The measurement layer consists of 4 autonomous objects: current measurement, velocity measurement, position measurement, and timer. The control layer consists of 3 autonomous objects: position control, velocity control, and current control. The position and velocity control object are constructed by fuzzy inference algorism in order to build doctors' and engineers' knowledge into the VAD control. The object manager paces events on each object in order to maintain time series processes. The control system can he adapted to an axial flow VAD by exchanging the position measurement and position control object into a flow estimation and flow control object. In vitro experiment showed that The VAD was driven stably enough to maintain cardiac function by cooperation of independently operated each object like cells in the control system. In conclusion, the above results shows that the autonomous distributed control system promises suitability as a new superior artificial control system.

This chapter presents a strategy for controlling the concentration of dissolved oxygen (DO) in the bioreactor of a pilot wastewater plant (WWTP). The control strategy being developed is model-based predictive control (MPC). To apply the control algorithm, the estimation of the oxygen transfer function (KLa) is first performed, then the model and linearization technique are determined and finally the MBPC controller is designed. The results are simulated in MATLAB® and executed in the plant control and supervision system Supervisory Control and Data Acquisition (SCADA) in LabVIEWTM. This chapter is organized as follows: Section 1 presents a brief introduction, and Section 2 determines and describes the model to be used and its respective linearization, as well as the results obtained for the KLa parameter. Finally, Section 3 describes the design methodology of the generalized predictive control (GPC) controller proposed by Clarke, using the Model Predictive Control Toolbox and the EPSAC strategy developed by De Keyser. It should be noted that the simulations in each of the sections were performed in MATLAB® and executed in the control and supervision system with the MATLAB® script interface in LabVIEWTM.

The authors introduce a multifunctional control research test bench and its data management and interface system. They implemented a building monitoring, control, and interface system (MCIS) used for evaluation of complex building energy systems, for optimization of such energy systems and for carrying out control research experiments. In this paper they explain the MCIS' architecture and functionality, they present its research potential and three different control research use cases for building energy systems and heating, ventilation, and air conditioning (HVAC) systems; model-assisted control parameter fine tuning, model-based predictive control, and demonstration of adaptive control algorithms. The authors outline prerequisites for implementation, demonstration, and evaluation of new developed control algorithms and strategies. These prerequisites are fulfilled via system expansions providing a flexible demonstration bench.

Reducing the energy footprint of grinding circuits: the process control paradigm