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Limited capacity and short life cycle of a battery are the major impediments in development of practical Electric Vehicles (EVs). Eco-driving is an optimization technique through which a velocity trajectory that consumes minimum energy is advised to the driver. However, presence of traffic signals to control large traffic network degrades the performance of eco-driving; as applying brakes to stop and then maximum re-acceleration to restart a trip consumes lot of energy. Eco-driving problem with multiple traffic signals and static model of battery has been proposed as Two Point Boundary Value Problem (TPBVP). TPBVP fails to solve multi-phase problem as a single phase due to discontinuity of the co-states at the junction, that is, start of a new phase. This paper investigates an optimal solution with both EV and battery dynamics in the presence of multiple traffic signals as Multi Point Boundary Value Problem (MPBVP) using multiple shooting technique. Traffic signals come at some intermediate points of a trip. MPBVP ensures continuity at the junction to solve the multi-phase problem as a single phase through inter dependencies between each phases. Goal of this work is not only to solve constrained eco-driving problem with traffic signals but also include charging and discharging limits on battery that indirectly improves battery’s life cycle. Results indicate that EV has crossed all the traffic signals during their green duration without applying brakes with also satisfying all the other constraints and continuity condition. Moreover, it can be seen that energy consumption using MPBVP is also marginally lesser as compared to TPBVP.

Electric vehicles (EVs) powered by electric motors and batteries have solved the issues related to the environmental pollution. The major concern with electric vehicles is their short range, which is due to the limited capacity of a battery installed in the system. Limited range issue can be solved or minimized through eco-driving; an optimization technique in which a driver is advised to follow a velocity profile that consumes minimum energy. In the recent past, eco-driving problem with an online requirement using the static model of a battery has been discussed. Eco-driving problem has been formulated as an optimal control problem, where the goal is to minimize vehicle power consumption only. In this work, the goal is extended to increase the life cycle of battery along with power consumption. For this purpose, battery dynamics are included along with vehicle dynamics. To increase the battery’s life cycle constraints are applied to avoid the battery from getting fully charged and discharged. Problem is solved using pontryagin’s minimum principle (PMP), where initial and final position of a vehicle, initial velocity of a vehicle and total trip time is fixed. Optimal torque, optimized velocity trajectory and constrained state of charge during a trip are generated that in turn minimize the energy consumption of the battery. The results have shown that constrained case is approximately 7 percent more efficient in terms of energy consumption than an unconstrained case. Reduction in energy consumption, coupled with battery constraints result in proper charging and discharging of the battery thereby extending battery life.

From the last few years, there has occur an increase in number of cars, which has badly affected our transport system and specially traffic on the roads. Traffic congestion and traffic accidents are the major concerns due to an increase in number of vehicles. Many efforts have been made in the last few years to improve safety and comfort in vehicular system. One of present focus is intelligent transport system (ITS) to ensure safety and comfort for the passenger. The main focus of this paper is to control the longitudinal dynamics of a vehicle, which make sure that a safe distance is kept between the leading and following vehicle. The major drawback with the existing control techniques is the inability to perform well in the presence of various parameters, which vary with the variation in the external factors like temperature and etc. This paper focuses on the development of a sliding mode control (SMC) for the longitudinal dynamics of automotive vehicle in a platoon system. System response will be observed in the presence of parametric uncertainty. First order and Second order sliding mode is applied and results are compared by comparing chattering in both the cases.

This paper describes the modeling and controlling of longitudinal vehicle model. State space averaging is used to get the nominal model of vehicle, while bond graph methodology is adopted to model the actuator dynamics of the vehicle. Robust control theory is applied to modify the nominal model to standard format used for parametric and multiplicative input uncertainties. H∞ control technique is adopted to control the states of the model in the presence of uncertainties and disturbance. Concept of servo mechanism is used to check velocity-tracking performance, while μ analysis is performed on the controlled model to check the robust stability and robust performance of the model.