Special issue on on-board optimization strategy design methods for connected hybrid electric vehicles

Tielong Shen·Carlos Guardiola·Fuguo Xu

As a trend in the innovation of automotive engineering，connectivity provides new opportunities and challenging issues for vehicular powertrain control due to big potential in the use of the connected information for improving energy efficiency and reducing CO2emission. In real world driving situation， a bottleneck for achieving optimal energy efficiency via control of the power sources in the powertrain is the uncertainty in power demand，since the power demand is delivered by the driver according to the driving environment which is always with stochasticity and un-detectable event in the environment. The connectivity enables us to predict the power demand in advance by using the real-time information of vehicle-to-vehicle， vehicle-to-infrastructure， and vehicle-to-cloud etc.，this new configuration for hybrid powertrain control excites innovative research for optimization of connected vehicles.This special issue focuses on the latest development，trends，and novel techniques for the design of on-board optimization strategies for hybrid electric vehicles (HEVs) under the connected environment. Especially，a special section is included that corrects several papers on new challenging solutions of the 6th IFAC Conference on Engine and Powertrain Control， Simulation and Modeling (IFAC ECOSM 2021) Benchmark Competition， where a real-time energy management problem with vehicle-toeverything(V2X)information is targeted for a typical HEV.

There are eleven papers collected in this special issue.The collections are divided into three groups.The first group，including seven papers，focuses on the solution of benchmark challenging problem of IFAC ECOSM 2021. F. Xu et al.，proposing this benchmark problem of developing real-time optimization algorithm for HEVs in V2X communication environment， describe the detail information of benchmark challenging problem，including the simulator，the challenging issue and the evaluating standard.It is concluded that the solutions from the challengers are hierarchical optimization architectures.In the paper from X.Jiao et al.，the conditional linear Gaussian is employed to predict future preceding vehicle’s speed and a DP-based energy management strategy is designed.B.Zhang et al.propose a rule-based controller to maintain safe driving and the Gaussian process regression is used to predict preceding vehicle speed， which is used for the calculation of ego demand torque in the HEV powertrain control. J. Gao et al. also develop a layered optimization framework，where ECMS is used for the torque distribution control of HEV powertrain.The solution from Y.Yamasaki et al.is designing a rule-based controller to determine ego vehicle’s speed and proposing the equivalent fuel consumptions in motors for HEV powertrain control.In the proposal from S. Dong et al.， model predictive control (MPC) is used for speed planning and an explicit solution is obtained for HEV powertrain control.T.Namerikawaetal.develop a hierarchical MPC framework for the NOxemission reduction and fuel economy improvement.

The second group collects two papers that focus on the powertrain control of gasoline vehicle and braking control of heavy-duty vehicle， respectively. In W. Cao’s work， the engine on/off scenario is optimized to improve fuel economy.K.Sekiguchi et al.develop a stochastic MPC-based braking control for heavy-duty vehicles with a Kalman filter-based state estimation， the effectiveness of proposed algorithm is verified in TruckSim platform.

The third group covers two papers on driver behavior prediction and vehicle routing problem， which are highly relevant to powertrain control and V2X. The paper by S.Kim et al.proposes an artificial neural network-based human driver characteristics estimator in accelerator scenario for both gasoline vehicle and plug HEV experimental platforms.Y.Wu et al.address the energy delivery problem of electric vehicles to serve a set of customers with consideration of terrain grade.

The guest editors hope this special issue could provide a new inspiration for these working in the field of powertrain control and motion control of connected and automated HEVs.We deeply appreciate Prof.Y.Hong，Editor-in-Chief of Control Theory and Technology，for his timely organization of this special issue and we are thankful to the staff in supporting this special issue. Moreover， the guest editors would like to thank the authors for their contributions to this special issue and the reviewers for their valuable evaluations to the manuscripts. Finally， we would like to express our thanks to Toyota Motor Corporation Japan for their continuous technical support to the simulator of benchmark challenging.