Olivier Grondin

Energy management strategy for Diesel hybrid electric vehicle

This paper focuses on hybrid energy management for a Diesel hybrid electric vehicle (HEV). The paper presents an adaptation of the equivalent consumption minimization strategy (ECMS) dedicated to the Diesel HEV control issues. The purpose of this paper is to introduce an additional degree of freedom into the ECMS that allows to modify the optimization tradeoffs from the pure fuel economy case to the pure NOx limitation case. The influence of this weighting parameter is evaluated for several engine configurations. The main contribution of this paper is to provide tools and methods to deal with the Diesel HEV control task. This paper applies a methodology based on SiL and HiL simulations in order to understand the system performance according to the powertrain configurations and also to tune the proposed energy management strategy. The simulation results are confirmed by experiments performed on hybrid-hardware in the loop (Hy-HiL) test bench. These results demonstrate the ability of the proposed strategy to reduce the NOx emissions while maintaining a reasonable fuel consumption. This result is mostly due to the ability of the modified ECMS to operate the Diesel engine within its LTC region where the NOx emissions are very low.

Control of a two stage turbocharger on a Diesel engine

Two stage turbochargers have been developed recently for Diesel engines in order to improve their performances in terms of power, consumption, emissions and dynamic behavior (see [1]). For this kind of system, the operating conditions are very different than for one stage turbochargers and specific control issues must be considered. In this paper an analysis of single stage turbochargers control issues is extended to two stage systems in order to highlight the specific issues. Two control structures able to cope with these problems are proposed and compared experimentally. A particular focus has been put on industrial constraints such as the number of sensors, the calibration effort, and a robustness analysis. Vehicle results demonstrate the relevance of the strategies proposed and illustrate the analysis.

Model Based Control of Turbochargers: Application to a Diesel HCCI Engine

The recent developments in Diesel engines tend towards new types of combustion, such as Homogeneous Charge Compression Ignition (HCCI) which looks promising with respect to the pollutant emissions. However, these new technologies require a faster and more accurate control of the gas mixture in the cylinder due to its higher sensitivity to thermodynamic conditions and composition. A major issue in the development of these new types of Diesel engines lies in the architecture and the control of the air intake system. In this context many setups are envisaged, and in particular the turbocharging systems are becoming more and more complex: variable geometry turbines, double stage turbochargers, variable geometry compressors. The associated control laws have to be modified: the conventional strategies based on steady static maps and proportional integral controllers have to be improved in order to address the new challenges. This paper proposes a model based control strategy for a variable geometry turbocharger. This strategy is based on a physical representation of the system (turbocharger, intake and exhaust manifolds). The approach has two main advantages: it is easy to calibrate, and it can be adapted to other types of architecture. The first part of this paper describes the architecture of the system and its model. The second part details the strategies designed and the results carried out in simulation and on an engine test bed.

Combustion parameters estimation and control using vibration signal : Application to the Diesel HCCI engine

This paper proposes a method to estimate and to control the combustion timing of a diesel homogeneous charge compression ignition (HCCI) engine without cylinder pressure transducers. The principle of the proposed controller is to correct the start of injection (SoI) in order to compensate the effects of the air path errors or injection system perturbation. The controller takes as inputs the middle of combustion estimated from the vibration trace recorded with a knock sensor fitted at the surface of the engine block. The estimated combustion parameters are computed in real-time and sent to the engine control system in a cycle to cycle manner. The contribution of this paper is combustion state estimator and controller that allows to maintain the desired combustion timings. Tests are performed on a test bench to compare the estimated and measured combustion timing. The closed-loop controller is validated in steady engine conditions and the obtained results demonstrate the potential of this approach.

Transient Torque Control of a Diesel Hybrid Powertrain for NOx Limitation

Abstract This paper describes a strategy for the reduction of the transient nitrogen oxides (NO x ) emissions in a diesel hybrid electric vehicle (HEV). This strategy limits the dynamics of the engine by using the electric motor to maintain the wheel torque demand. Thus, the split ratio between the motor and the engine, initially computed from a steady-state optimal control strategy, is corrected during transient operations where NO x are produced. The engine torque correction relies on mean value models for the EGR system dynamics and for the NO x formation. The strategy is combined with a static EMS and implemented into a software in the loop platform including a detailed engine model with NO x prediction capabilities. This model based approach for the transient engine torque limitation allows a significant NO x reduction with a limited increase in the fuel consumption.

ECMS Controller Robustness in Flex-Fuel Hybrid Vehicles

Control algorithms for hybrid vehicles have undergone extensive research and development leading to near-optimal techniques being employed and demonstrated in prototype vehicles over the previous decade. The use of different implementations of optimal controllers is inevitably linked through the assumed knowledge of the system being controlled. With the growing interest in alternative fuels, such as ethanol, liquified petroleum gas (LPG), and compressed natural gas (CNG) due to enhanced emissions and fuel security considerations, a natural extension is to hybridize these engines to improve fuel economy and CO2 emissions. This step is complicated by the potential variation in fuel composition seen with many gasoline and diesel alternatives, leading to uncertainty in the models used by the hybrid powertrain controller. This work investigates the robustness of one hybrid powertrain optimal control approach, the equivalent consumption minimization strategy (ECMS). Two case studies are performed involving experimentally obtained engine maps from two significantly different prototypes flex-fuel vehicles to quantify the potential impact of map error caused by incorrect fuel assumptions. [DOI: 10.1115/1.4027561]

Torque-oriented control of an homogeneous charge compression ignition vehicle

This paper presents a torque-oriented structure designed for a diesel homogeneous combustion compression ignition (HCCI) engine control. The proposed controllers are designed to get the maximum benefit provided by the HCCI combustion system. The engine control issues comes from the sensitivity of the HCCI combustion system and from the complexity of the intake system. The proposed control structure combines several controllers presented in previous papers. Each controller is adapted in order to takes into account of the constraints inferred by this specific engine architecture and combustion system. The air path controller copes with a nonlinear coupled multivariable system. The fuel path controller is designed to ensure a good coordination with the airpath system dynamic. These two aspects with the corresponding control strategies are presented in this paper. The HCCI engine is embedded into a demonstration car and the torque structure is adapted accordingly. The controller performances are evaluated during New European Driving Cycle (NEDC) at the rolling test bed.

State of Charge Management for Plug-In Hybrid Vehicles With Uncertain Trip Information

Efficient state of charge management of plug-in hybrid electric vehicles (PHEVs) differs from their nonplug-in counterparts through the utilization of a charge depleting (CD) mode of operation. Several studies have shown that a blended mode of CD holds fuel economy advantages over a CD and charge sustaining (CS) combination, however, these approaches assume knowledge of the total journey distance. Here, this assumption is relaxed and the state of charge trajectory was recalculated online using a weaker assumption that only a probability distribution accumulated over past trips is available. The importance of other contributing factors to the state of charge profile such as vehicle velocity and altitude is also assessed. Simulation results on a prototype plug-in hybrid are presented with an adaptive equivalent consumption minimization strategy (ECMS) used by the powertrain management to track the proposed state of charge trajectory. The financial and environmental benefits of the proposed approach relative to other state of charge management strategies are then calculated over a number of different cycles and conditions. [DOI: 10.1115/1.4030428]

Rapid-prototyping multi-sensors processing platform for real time engine control and diagnosis

Abstract Future internal combustion engine technologies require an accurate combustion monitoring and control. This can be performed through high frequency recordings and processing of combustion related variables such as cylinder pressure or knock signals. This paper presents a flexible rapid prototyping system based on xPC target which can be used for multi sensor recordings and for signal processing algorithm developments. After a description of the platform hardware and software, an example of combustion analysis based on cylinder pressure and accelerometer signals is given. The paper ends with a comparison of direct and indirect combustion parameters computation in real time for closed loop combustion control purpose.

State of charge management for plug in hybrid electric vehicles with uncertain distance to recharge

The state of charge management of plug in hybrid vehicles differs from their non-plug in counterparts through the utilisation of a charge depleting mode of operation. Several studies have shown that a blended mode of charge depletion holds fuel economy advantages over a charge depletion and charge sustaining combination, however these approaches assume knowledge of the total journey distance. Here, this assumption is relaxed and the state of charge trajectory recalculated online using a weaker assumption that only a probability distribution accumulated over past trips is available. The benefits relative to other potential strategies are assessed in terms of relative fuel consumption and tailpipe CO2 emissions.