Vehicle traction control system has been developed to enhance the capability and direction stability of driving wheels through tyre slip ratio regulation. Under normal situations, if exceeds a certain threshold, wheel is regulated by coupled interaction engine torque active brake pressure. In order obtain best performance on road under complicated friction conditions, pressure, need be decoupled adjusted avoid penalisation each other. this paper, coordinated cascade method with two...

The rapid development of the Internet Things (IoT) and cloud computing has presented unprecedented opportunities challenges for automotive industry. As additional traffic data becomes accessible, powertrain capability to employ sophisticated control algorithms in order enhance fuel efficiency. This study presents a hierarchical strategy commuter plug-in hybrid electric vehicles (PHEVs), incorporating historical driving real-time conditions. Firstly, upper layer, an iterative learning...

Automotive powertrain mainly consisting of combustion engine, motor and battery (i.e. special for hybrid powertrain) is a very complicated integration system, the research on automotive control techniques remains hot-spot in past decades. This paper proposes some challenging issues solutions system from perspective dynamic theory. The typical characteristics are analysed development, several applications using model-based model-free design demonstrated with sufficient experimental...

The electronic throttle system (ETS) is one of the important components an automobile engine that adjust air intake to directly affect combustion power engine. In practical scenarios, proportional–integral–derivative (PID) a common and effective method. However, traditional PID difficult satisfy ETS performance requirements, e.g., response overshoot not allowed exist. Moreover, controller gains are also tune manually. To tackle abovementioned issues, we propose signal compensation control...

This paper presents a model predictive online optimization scheme for the engine torque control problem. The control-oriented is based on intake air charging dynamics and generation which are derived from mean value model. In order to reduce tracking error induce by insufficient accurate model, an embedded integrator about designed. Then, algorithm namely C/GMRES adopted solve nonlinear optimal Finally, experimental validations conducted demonstrated robustness transient performance proposed...

In this paper, an analytic constrained nonlinear state feedback for torque control of a gasoline engine is designed. The based on the mean-value model engine, which consists intake manifold air filling dynamics and calibration equation. proposed can be made as close possible to minimum-time controller by adequately choosing specific parameter controller. Illustrative experiments are assess efficiency Comparing performance Model Predictive Control (MPC), solution suggests that far underlying...

This paper proposes an experimental comparison between two optimal controllers for automotive spark ignition engines, including gain-scheduled linear quadratic regulation (LQR) controller and model predictive (MPC). The aim of the study is to highlight control effects LQR MPC scheme on specific engine problem, provide a reference future design. problem formulated ensure fast torque tracking performance, meanwhile improve thermal efficiency by reducing pumping loss. nitrogen oxide emission...

Model predictive control (MPC) have received wide attention in many industrial field owing to its optimization capability for the practical plant with constraints. However, performance of closed-loop system is rarely considered MPC design. In this paper, a relatively simple tuning approach MPC-based engine speed investigated based on inverse linear quadratic (ILQ) regulator design technique. Considering nonlinear and time-varying properties system, tracking dynamical deduced from mean value...

This paper proposes a model-based optimal control approach for automotive gasoline engines to achieve the torque tracking with lower pumping loss. The reduced engine dynamic model involving multi-input-multi-output framework is derived based on mean-value theory and polynomial fitting technique. Then controllers gain-scheduled LQR scheme designed high efficient purpose. Simulation validations are conducted validate effectiveness of proposed controller.

This paper presents a Lyapunov-based feedback design approach to set-point regulation problem of combustion engines. To enable the approach, mean-value model gasoline engine is proposed by experiment-based calibration torque generation. Then, state control law deduced in fashion Lyapunov stability, and extended case adaptive control. demonstrate schemes, simulation-based validation results will be shown finally with two stages, test stand-alone driving scenario under energy management hybrid...

Automotive engine is a sophisticated dynamical control system involving both continuous-time dynamic behavior and event-based cyclic state transition. To grasp the dynamics accurately, this paper proposes hybrid model structure for automotive gasoline engines that not only consists of continuous air path model, actuator response but also includes residual gas mass combustion process model. The proposed adopts an extended Kalman filter to on-line estimate it has potential be applied real-time...

This paper presents a control scheme of engine-dynamometer system performing real gasoline engine operation in virtual driver-vehicle-road simulation conditions. The focus is on the transient behavior dynamometer speed during engine-in-the-loop simulation, and control-oriented model constructed. Based model, generalized predictive controller designed as external loop existing to improve response system, which reduces synchronizing error between actual driveline-vehicle model. performance...

This paper proposes an engine speed tracking controller based on the MPC scheme and investigates a tuning method for practical control performance from viewpoint of ILQ design. First, nonlinear system dynamics mean-value model is transformed to linear error by feedback linearization method. Then designed derived dynamical model. To achieve convenient adjustment performance, quadratic weightings in index are calculated with respect single parameter means inverse optimality conditions LQ...

Plug-in hybrid electric vehicles offer an opportunity to reduce emissions and Energy management strategies (EMS) are the key improving fuel economy of PHEVs. With rise artificial intelligence, deep reinforcement learning (DRL) is a promising approach for building energy vehicles. For novel single-shaft series-parallel powertrain, we propose deterministic policy gradient strategy combined with pre-optimization. Firstly, regard power distribution two motors in this powertrain as static...

This paper presents a multi-variable optimal controller design based on model predictive control (MPC) scheme for automotive gasoline engines. The aims to achieve fast torque tracking with the lower pumping loss, by tuning throttle valve angle and intake timing. To this end, nonlinear engine was built mean-value modeling theory polynomial technique, MPC is designed derived linearized model. performance validated full scale in real time. experimental results demonstrate effectiveness of...